\nAbout Commonwealth Fusion Systems: \n\n\nCommonwealth Fusion Systems is on a mission to deliver the urgent transition to fusion energy.\n\n\nCombining decades of research, top talent and new technologies, we’re designing and building commercially viable fusion power plants. And working with policymakers and suppliers to build the energy industry of the future. \n\n\nWe’re in the best position to make it happen. Since 2018, we’ve raised over $2 billion in capital – more than any other fusion energy company in the U.S.\n\n\nNow we’re looking for more thinkers, doers, builders, and makers to join us. People who’ll bring new perspectives, solve tough problems, and thrive as part of a team. \n\n\nIf that’s you and this role fits, we want to hear from you.\n\n\nJoin the power movement as a Senior Scientific Software Engineer\n\n\nThe Scientific Software team at CFS develops software that helps us understand and build superconducting magnets and tokamaks. The primary project for this role will be developing software for a fiber optic quench detection system. A quench is an event where a superconducting magnet goes into thermal runaway, and SPARC will incorporate a system using fiber optic cables to detect and mitigate these events. We seek an experienced software engineer (Senior to Principal level) to help develop an algorithm for detecting quenches based on the data received by the fiber optic system. \n\n\nOne of the tools used to develop the algorithm is a fiber model written in Python that simulates the expected signals during a quench and nominal operations. The engineer will also help increase the accuracy and performance of the simulation. The development of the fiber model and the quench detection algorithm are informed by experiments, ranging from bench top tests to full sized magnets. The engineer will be responsible for analyzing experimental data from these tests to validate the fiber model and test and develop the quench detection algorithm.\n\n\n\nWhat you'll do:\n* Rapidly learn and improve complex physics-based models and simulations from first principles optics and physics\n* Enhance quench detection algorithm performance (i.e. reduce quench detection false positive and false negative rates), by applying image and signal processing techniques to time-series spectral data\n* Collaborate with cross-functional teams, including the physics, production, and SPARC Software (real-time controls) teams, to identify and execute on key data and algorithm needs\n* Clearly communicate technical results and project progress\n* Develop, implement, and maintain CI/CD pipelines to streamline development processes, ensure code reliability, and reduce operational overhead\n\n\n\nWhat we’re looking for:\n* Bachelor’s degree in a technical field preferred\n* Programming language: Python, including type hinting and object-oriented features.\n* Basic understanding of numerical methods, linear algebra, and differential equations.\n* Understand the basics of the project’s physics aspects (e.g., undergrad-level electromagnetics and optics)\n* Data analysis using pandas, numpy, matplotlib, or other similar Python packages\n* Experience with at least one of the following: signal processing, machine learning, and data analytic tools\n\n\n\nBonus points for: \n* Programming languages: C++, Rust, or experience with low-level performance and memory management\n* Concurrency and parallelization\n* Demonstrated experience building a simulation framework that uses physics-based modeling\n\n\n\nMust-have Requirements: \n* Perform activities such as typing or sitting for extended periods of time\n* Dedication to safety to mitigate industrial hazards that may include heat, cold, noise, fumes, strong magnets, lead (Pb), high voltage, and cryogenics\n* Willingness to travel or work required nights/weekends/on-call occasionally\n\n\n\n\n\n$140,000 - $200,000 a yearSalary range for this full-time position + equity + benefits. The actual salary will depend on level, location, qualifications, and experience. The range displayed on each job posting reflects new hire salaries for the position across all US locations. Benefits include:•  Competitive compensation with equity•  12.5 Company-wide Holidays•  Flexible vacation days•  10 sick days•  Generous parental leave policy•  Health, dental, and vision insurance•  401(k) with employer matching•  Professional growth opportunities•  Team-building activities\n\n#LI-Remote\n\n\nAt CFS, we excel in fast-paced environments, driven by our values of integrity, execution, impact, and self-critique. As we grow, we’re eager to bring on mission-driven folks who offer diverse perspectives and fresh ways to tackle challenges.\n\n\nWe value diversity deeply and are proud to be an equal opportunity employer by choice. We consider all qualified applicants equally, regardless of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Python, Senior and Engineer jobs that are similar:\n\n $60,000 — $135,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nDevens, MA

\nWe are looking for a Senior Machine Learning Engineer to join our Knowledge Enrichment team at BenchSci. \n\n\nYou will help design and implement ML-based approaches to analyse, extract and generate knowledge from complex biomedical data such as experimental protocols and from results from several heterogeneous sources, including both publicly available data and proprietary internal data, represented in unstructured text and knowledge graphs. You will work alongside some of the brightest minds in tech, leveraging state of the art approaches to deliver on BenSci’s mission to expedite drug discovery. Knowledge Enrichment is at the core of this challenge as it ensures we can reason over and gain insights from an extensive, accurate, and high quality representation of biomedical data.\n\n\nThe data will be leveraged in order to enrich BenchSci’s knowledge graph through classification, discovery of high value implicit relationships, predicting novel insights/hypotheses, and other ML techniques. You will collaborate with your team members in applying state of the art ML and graph ML/data science algorithms to this data. \n\n\nYou are comfortable working in a team that pushes the boundaries of what is possible with cutting edge ML/AI, challenges the status quo, is laser focused on value delivery in a fail-fast environment.\n\n\n\nYou Will:\n* Analyse and manipulate a large, highly-connected biological knowledge graph constructed of data from multiple heterogeneous sources, in order to identify data enrichment opportunities and strategies.\n* Work with data and knowledge engineering experts to design and develop knowledge enrichment approaches/strategies that can exploit data within our knowledge graph.\n* Provide solutions related to classification, clustering, more-like-this-type querying, discovery of high value implicit relationships, and making inferences across the data that can reveal novel insights.\n* Deliver robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency.\n* Architect and design ML solutions, from data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and monitoring.\n* Collaborate with your teammates from other functions such as product management, project management and science, as well as other engineering disciplines.\n* Sometimes provide technical leadership on Knowledge Enrichment projects that seek to use ML to enrich the data in BenchSci’s Knowledge Graph.\n* Work closely with other ML engineers to ensure alignment on technical solutioning and approaches.\n* Liaise closely with stakeholders from other functions including product and science.\n* Help ensure adoption of ML best practices and state of the art ML approaches within your team(s).Participate in various agile rituals and related practices.\n\n\n\nYou Have:\n* Minimum 3, ideally 5+ years of experience working as an ML engineer.\n* Some experience providing technical leadership on complex projects.\n* Degree, preferably PhD, in Software Engineering, Computer Science, or a similar area.A proven track record of delivering complex ML projects working alongside high performing ML, data and software engineers using agile software development. Demonstrable ML proficiency with a deep understanding of how to utilise state of the art NLP and ML techniques.\n* Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch. Extensive experience with Python and PyTorch.\n* Track record of contributing to the successful delivery of robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency.\n* Experience with the full ML development lifecycle from architecture and technical design, through data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and maintenance.\n* Familiarity with implementing solutions leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture.\n* Experience with graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with biological ontologies.\n* Experience with complex problem solving and an eye for details such as scalability and performance of a potential solution.\n* Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python.\n* Experience with data manipulation and processing, such as SQL, Cypher or Pandas.A can-do proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do; you will excel best if this environment suits you.\n* You have experience working in cross-functional teams with product managers, scientists, project managers, engineers from other disciplines (e.g. data engineering).Ideally you have worked in the scientific/biological domain with scientists on your team.\n* Outstanding verbal and written communication skills. Can clearly explain complex technical concepts/systems to engineering peers and non-engineering stakeholders.\n* A growth mindset continuously seeking to stay up-to-date with cutting-edge advances in ML/AI, complimented by actively engaging with the ML/AI community.\n\n\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Python, Senior and Engineer jobs that are similar:\n\n $60,000 — $110,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nToronto, Ontario

\nWe are looking for a Senior Machine Learning Engineer to join our Knowledge Enrichment team at BenchSci. \n\n\nYou will help design and implement ML-based approaches to analyse, extract and generate knowledge from complex biomedical data such as experimental protocols and from results from several heterogeneous sources, including both publicly available data and proprietary internal data, represented in unstructured text and knowledge graphs. You will work alongside some of the brightest minds in tech, leveraging state of the art approaches to deliver on BenSci’s mission to expedite drug discovery. Knowledge Enrichment is at the core of this challenge as it ensures we can reason over and gain insights from an extensive, accurate, and high quality representation of biomedical data.\n\n\nThe data will be leveraged in order to enrich BenchSci’s knowledge graph through classification, discovery of high value implicit relationships, predicting novel insights/hypotheses, and other ML techniques. You will collaborate with your team members in applying state of the art ML and graph ML/data science algorithms to this data. \n\n\nYou are comfortable working in a team that pushes the boundaries of what is possible with cutting edge ML/AI, challenges the status quo, is laser focused on value delivery in a fail-fast environment.\n\n\n\nYou Will:\n* Analyse and manipulate a large, highly-connected biological knowledge graph constructed of data from multiple heterogeneous sources, in order to identify data enrichment opportunities and strategies.\n* Work with data and knowledge engineering experts to design and develop knowledge enrichment approaches/strategies that can exploit data within our knowledge graph.\n* Provide solutions related to classification, clustering, more-like-this-type querying, discovery of high value implicit relationships, and making inferences across the data that can reveal novel insights.\n* Deliver robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency.\n* Architect and design ML solutions, from data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and monitoring.\n* Collaborate with your teammates from other functions such as product management, project management and science, as well as other engineering disciplines.\n* Sometimes provide technical leadership on Knowledge Enrichment projects that seek to use ML to enrich the data in BenchSci’s Knowledge Graph.\n* Work closely with other ML engineers to ensure alignment on technical solutioning and approaches.\n* Liaise closely with stakeholders from other functions including product and science.\n* Help ensure adoption of ML best practices and state of the art ML approaches within your team(s).Participate in various agile rituals and related practices.\n\n\n\nYou Have:\n* Minimum 3, ideally 5+ years of experience working as an ML engineer.\n* Some experience providing technical leadership on complex projects.\n* Degree, preferably PhD, in Software Engineering, Computer Science, or a similar area.A proven track record of delivering complex ML projects working alongside high performing ML, data and software engineers using agile software development. Demonstrable ML proficiency with a deep understanding of how to utilise state of the art NLP and ML techniques.\n* Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch. Extensive experience with Python and PyTorch.\n* Track record of contributing to the successful delivery of robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency.\n* Experience with the full ML development lifecycle from architecture and technical design, through data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and maintenance.\n* Familiarity with implementing solutions leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture.\n* Experience with graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with biological ontologies.\n* Experience with complex problem solving and an eye for details such as scalability and performance of a potential solution.\n* Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python.\n* Experience with data manipulation and processing, such as SQL, Cypher or Pandas.A can-do proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do; you will excel best if this environment suits you.\n* You have experience working in cross-functional teams with product managers, scientists, project managers, engineers from other disciplines (e.g. data engineering).Ideally you have worked in the scientific/biological domain with scientists on your team.\n* Outstanding verbal and written communication skills. Can clearly explain complex technical concepts/systems to engineering peers and non-engineering stakeholders.\n* A growth mindset continuously seeking to stay up-to-date with cutting-edge advances in ML/AI, complimented by actively engaging with the ML/AI community.\n\n\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Python, Senior and Engineer jobs that are similar:\n\n $60,000 — $110,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nLondon, England

\nSurveyMonkey is a global leader in online surveys and forms that empowers people with the insights they need to make decisions with speed and confidence. Our fast, intuitive feedback management platform connects millions of users worldwide with real-time AI-powered insights that drive meaningful decisions. We provide answers to more than 20 million questions every day so that people and organizations can attract new audiences, delight customers, create advocates, and extend their competitive advantage in the marketplace. Our vision is to raise the bar for human experiences by amplifying individual voices. Learn more at surveymonkey.com.\n\nWhat we’re looking for\n\nWe are looking for a seasoned Staff Data Engineer with amazing problem-solving abilities and a growth mindset to join a team of highly skilled data engineers and data architects to build and manage the end-to-end data pipelines (batch and near real-time) using modern cloud technologies. This is a role in the central data organization at SurveyMonkey that provides actionable insights to all key business functions of the organization\n\nAs a Staff Data Engineer, you will lead data engineering initiatives and build end-to-end Analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You will be reporting to the Director of Data Engineering\n\nWhat you’ll be working on\n\n\nDesign, architect and build data pipelines to support existing data models \n\nManage the Data Infrastructure & Platform\n\nData quality: Build quality checks in the end-to-end data pipelines\n\nDesign & Build new Data models (Fact vs Dimension). Write performant/idempotent transformations in Snowflake using dbt \n\nBuild data pipeline using Python scripting (in a modular/loop context) Write well-tested, production-ready code in Python and Snowflake SQL\n\nHands-on experience implementing ETL (or ELT) best practices \n\nTranslate business requirements, to technical specifications,  form project scope, and deliver deployable code.\n\nWrite complex data engineering Snowflake - SQL jobs that perform sophisticated queries on the entirety of our datasets\n\nDocument our systems for internal and external stakeholders\n\nMonitor and debug data pipelines running on Airflow\n\nParticipate in code reviews\n\nMentor data engineers on best practices and coding standards\n\nLead and collaborate effectively with cross-functional teams, including data scientists, analysts, and business stakeholders.\n\nIdentifying opportunities for process improvements, automation, and optimization of data pipelines. \n\nImplementing innovative solutions and exploring new technologies to address complex data challenges\n\n\n\n\nWe’d love to hear from people with\n\n\n8+ years experience in data engineering and Data warehousing technologies\n\n4+ years experience in Snowflake/ETL/ELT  or similar technologies like Redshift\n\nExperience building and scaling a Data Platform.\n\nExperience doing Proof of concept for new solutions and technologies \n\nExperience with AWS cloud services: S3, EC2, RDS, Spark, EMR etc\n\nExperience with object-oriented/object function scripting languages: Python (preferred), Java, Scala, etc.\n\nExperience in orchestrating, automating, and deploying production data pipelines using Airflow/Luigi, etc\n\nExtensive Experience with DevOps: Git, Github actions, CI/CD pipelines, Terraform, etc\n\nExperience with tools such as DBT or other similar technologies\n\nExperience with transforming, and developing data structures, metadata, dependency, and data workflows to support an Analytics function\n\nExperience with Designing Scalable Data Models in a Cloud Data warehouse\n\nIn-depth knowledge of Data lakes, EDW concepts, and data modeling (Star, Snowflake, and Galaxy schemas) \n\nExperience in implementing data governance practices and ensuring compliance with data privacy regulations (such as GDPR, CCPA).\n\nCommitment to continuous learning and professional development\n\n\n\n\nWhy SurveyMonkey? We’re glad you asked \nSurveyMonkey is a place where the curious come to grow. We’re building an inclusive workplace where people of every background can excel no matter their time zone. At SurveyMonkey, we weave employee feedback into everything we do to create forward-looking benefits policies, employee programs, and an award-winning culture, including best workplace for parents, our annual holiday refresh, our annual week of service, and our C.H.O.I.C.E Fund. In addition, we’ve reimagined the way we work to allow employees to choose what works best for them -- working in-person, fully remote, or a hybrid model that combines the two through our Choice Model.\n\nOur commitment to an inclusive workplace\nSurveyMonkey is an equal-opportunity employer committed to providing a workplace free from harassment and discrimination. We celebrate the unique differences of our employees because that is what drives curiosity, innovation, and the success of our business. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate. Accommodations are available for applicants with disabilities.\n\n#LI-remote \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Python, Cloud and Engineer jobs that are similar:\n\n $60,000 — $110,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nOttawa, Ontario, Canada

\nWhy Valence\nValence’s mission is to help the world work better, together with our first-to-market gen AI leadership and team coaching platform for F500 enterprises. We are only looking for high performing, driven, curious, and high ownership professionals to come join us in the next phase of building Valence. \n\n\nPioneered Gen-AI Coaching: Launched our groundbreaking AI product to market in just 2 months, swiftly concluding our beta in 8 weeks. We're ahead and accelerating.\nUnmatched B2B Speed: Sealed our first AI enterprise deal in 60 days, outpacing the standard 9-month cycle. The elite queue up for us.\nMasters in Enterprise SaaS Sales: Our tools were a staple in F500s like ExxonMobil and Coca Cola before we even completed venture funding. We set the standard.\nHumanizing AI Like No Other: Our AI coach offers unparalleled, intimate interactions that nurture growth at work. We’re a trusted, human-like partner to our users.\nHyper-Growth Innovators: We excel in rapid, experimental progress, learning and evolving faster than anyone else.\nElite Problem-Solvers: Our team, drawn from the top 1% with backgrounds in McKinsey and Bridgewater, tackles the toughest problems.\n\n\nFeatured in the Harvard Business Review (as “Shift”) and supported by world-class thinkers and leaders like Prasad Setty (Google) and William McNabb (Vanguard). \n\n\nThe Role\nWe are seeking a Senior Software Engineer for our LLM-powered coaching product that serves F500 enterprises. In this role you will actively build this AI product, support the technical architecture and roadmap, and work on a nimble, product-focused team that is bringing a revolutionary new enterprise product to market. You will report to the Technical Lead, and indirectly to the CEO, who is the product visionary for this new product.\n\n\nLocation and Work Environment\nThis is a primarily remote, work-from-home role with quarterly travel for team gatherings as able. Candidates must be comfortable balancing clients and colleagues in global timezones, as needed. Candidates must have valid ID/passports and must not have any restrictions on their travel abilities due to work authorization or permits.\n\n\n\nWhat You'll Do\n* Work with the product team to understand and prioritize evolving requirements.\n* Writing, reviewing, and deploying code.\n* Contribute to the technical roadmap, including architecture and development infrastructure.\n* Contribute to the product being scalable and maintainable.\n* Support managing and and breaking down large product and technical efforts.\n\n\n* Contribute to machine learning and large language model (LLM) pipelines and APIs, including OpenAI (GPT-3.5 and GPT-4), Azure (OpenAI), Anthropic (Claude), and others.\n\n\nIn The First Week, Expect To:\n* Deploy a feature.\n* Get up to speed on the product and the team.\n* Meet with the broader team and understand their roles and responsibilities.\n* Understand the technical architecture and roadmap.\n\n\nIn The First Month, Expect To:\n* Ship 1-2 major product features or technical enhancements.\n* Review the current engineering work and provide inputs on areas for improvement or prioritization.\n\n\n* Ship an LLM-powered coaching scenario.\n\n\nIn The First Three Months, Expect To:\n* Strategize and scope on multiple on large technical projects.\n* Drive improvements to our codebase and process to quickly build secure, maintainable software.\n* Ensure that all code is of high quality and is easily maintainable.\n\n\nIn The First 6-12 Months, Expect To:\n* Continue shipping work on major product initiatives.\n* Support the broader technical team and ensure that all work is executed efficiently and effectively\n* Become a critical member of the team that is responsible for the success of the product.\n* Take on additional responsibility as a senior member of Valence’s team.\n* Take the product to scale with dozens of Fortune 1000 companies and thousands of users.\n\n\n\nWhat We’re Looking For\n* Experience working with Python and Django\n* Experience working with AWS infrastructure (Elastic Container Service, Terraform, Relational Data Store, etc.) and Heroku\n* Experience with LLMs and ML/data is a plus\n\n\n* Experience managing and executing on large technical endeavors.\n* Experience owning a technical architecture and roadmap.\n* Exposure to early-stage startups, preferably B2B Saas.\n\n\n\nWhat you'll get\n* Ownership of projects and strategic priorities regardless of seniority in our learning-focused environment.\n* Frequent, tailored coaching and feedback sessions with managers deeply invested in your professional growth.\n* Strong ties to the executive team, a culture of transparency and engagement with strategic decisions.\n* Options from day one, which means you will be on the ownership track right away.\n* Competitive salary and equity packages.\n* Comprehensive health coverage (medical, dental, and vision) from day 1.\n* Virtual doctor and mental health services from day 1.\n* Provision of anything you need to be successful -  learning tools, hardware, office equipment, software.\n* Generous PTO, company-wide R&R shutdowns and paid leave for parents. \n* A WFH stipend, phone stipend and merch merch merch. \n\n\n\n\n\nDiversity Equity and Inclusion\nWe are committed to fostering a diverse and inclusive environment where our team members, vendors, contractors and beyond feel valued and supported. We know that our commitment to inclusion and belonging enables us to do our best work overall. We strongly encourage applications from candidates of all backgrounds regardless of race, gender, sexual orientation, marital status, age, citizenship, disability, and national origin. Accommodations are available upon request for candidates taking part in all aspects of the hiring and selection process. We know applying for a job can be intimidating, please don’t hesitate to reach out - Allison Langille, Head of People [email protected]. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to SaaS, Python, Senior and Engineer jobs that are similar:\n\n $60,000 — $110,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nNew York