This job post is closed and the position is probably filled. Please do not apply. Work for phData and want to re-open this job? Use the edit link in the email when you posted the job!
\nData Science and Big Data are all we do.\n\nIf you're inspired by innovation and passionate about driving customer success - this may be the ideal opportunity to leverage your systems engineering and automation experience to build and support Machine Learning platforms for the clients we serve.\n\nAt phData, our proven success has skyrocketed the demand for our services, resulting in quality growth and an expanded presence at our company headquarters located in downtown Minneapolis and in Bangalore, India.\n\nAs the world’s first and only Data Science Enablement services firm and the largest pure-play Big Data service provider, our team includes Apache committers, Machine Learning experts and the most knowledgeable Spark and Scala development team in the industry. phData has earned the trust of customers by demonstrating our mastery of Data Science and Big Data services along with our commitment to excellence.\n\nIn addition to phenomenal growth and learning opportunities, we offer competitive compensation and excellent perks including base salary, annual bonus, extensive training, paid certifications - in addition to generous PTO, a comprehensive benefits program and employee equity.\n\nMachine Learning Platform Architect\n\nAs a Machine Learning Platform Architect, you will serve as the guiding force in architecting and engineering Machine Learning platforms for enterprise clients. In this hands-on role, your responsibilities will include:\n\n\n* Help automate and deploy Machine Learning platforms and applications\n\n* Guide customers on the best practices of upgrades, patches, and maintenance\n\n* Deploy continuous integration and security\n\n* Maintain constant curiosity and a thirst for learning\n\n* Investigate product related issues both for individual customers and for common trends that may arise\n\n* Participate in occasional weekend on-call rotation for critical support needs\n\n* Provide a best-in-class customer experience\n\n\n\n\nRequired Experience:\n\n\n* 5-7 years of Linux Systems Engineering experience to include monitoring, patches, upgrades, and O/S support\n\n* Proven system/application automation and deployment experience using Ansible, Chef, Puppet or similar tools\n\n* Experience with Application Web Frameworks is a plus; Apache, Engenix, Tomcat, Spring, Flask, Play, etc is plus\n\n* Previous Consulting experience with external customers is highly preferred\n\n* Hands-on configuration with Security including LDAP, Active Directory\n\n* Passion for providing a great customer experience\n\n* Ability to work in a fast paced and agile environment\n\n* Excellent communication skills (written and verbal)\n\n* Strong problem-solving and analytical skills\n\n* Demonstrable troubleshooting skills\n\n* A positive attitude toward feedback and continual improvement\n\n\n\n\nPreferred Qualifications:\n\n\n* Working knowledge and experience with Python related technologies.\n\n* Understanding of networking, distributed systems, and Linux operating system concepts\n\n* Knowledge of relational database management systems (RDBMS), SQL and database concepts\n\n* On-the-job experience troubleshooting enterprise customer issues\n\n* Knowledge and experience with Kubernetes\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 Machine Learning, Architecture, Python, Scala, Apache and Linux jobs that are similar:\n\n
$80,000 — $125,000/year\n
\n\n#Benefits\n
๐ฐ 401(k)\n\n๐ Distributed team\n\nโฐ Async\n\n๐ค Vision insurance\n\n๐ฆท Dental insurance\n\n๐ Medical insurance\n\n๐ Unlimited vacation\n\n๐ Paid time off\n\n๐ 4 day workweek\n\n๐ฐ 401k matching\n\n๐ Company retreats\n\n๐ฌ Coworking budget\n\n๐ Learning budget\n\n๐ช Free gym membership\n\n๐ง Mental wellness budget\n\n๐ฅ Home office budget\n\n๐ฅง Pay in crypto\n\n๐ฅธ Pseudonymous\n\n๐ฐ Profit sharing\n\n๐ฐ Equity compensation\n\nโฌ๏ธ No whiteboard interview\n\n๐ No monitoring system\n\n๐ซ No politics at work\n\n๐ We hire old (and young)\n\n
# How do you apply?\n\nThis job post has been closed by the poster, which means they probably have enough applicants now. Please do not apply.
This job post is closed and the position is probably filled. Please do not apply. Work for Selerity and want to re-open this job? Use the edit link in the email when you posted the job!
\nSenior Machine Learning Engineer\n\nSummary:\n\nSenior Machine Learning Engineer to join Selerity’s team, scaling up an A.I. driven analytics and recommendation platform and integrating it into enterprise workflows. Highly competitive compensation plus significant opportunities for professional growth and career advancement.\n\nEmployment Type: Contract or Full-time\n\nLocation is flexible: We have offices in New York City and Oak Park, Illinois (Chicago suburb) but about half of our team currently works remotely from various parts of Europe, North America, and Asia. \n\n\nJob Description:\n\nWant to change how the world engages with chat, research, social media, news, and data?\n\nSelerity has dominated ultra-low-latency data science in finance for almost a decade. Now our real-time content analytics and contextual recommendation platform is gaining broader traction in enterprise and media applications. We're tackling big challenges in predictive analytics, conversational interfaces, and workflow automation and need your help!\n\nWe’re looking for an experienced Machine Learning Engineer to join a major initiative at a critical point in our company’s growth. This is a hands-on role, applying the latest technology in natural language processing and machine learning (including deep learning) to real-world problems in capital markets, institutional research, financial news, and social media. Machines are playing an ever-increasing role in finance and we're leading that trend.\n\n\nMust-haves:\n\n* Possess a rock-solid background in Computer Science (minimum BS in Comp Sci or related field) + at least 5 years (ideally 10+) of challenging work experience.\n\n* Rigorous understanding of data science foundations and theory including algorithms, statistics, experimental setup, etc.\n\n* Experience applying NLP and/or machine learning to large-scale datasets, especially text.\n\n* Experience with large-scale analytics and machine learning technologies including TensorFlow/Sonnet, Torch, Caffe, Spark, Hadoop, cuDNN, etc.\n\n* Advanced proficiency working in Java in Linux environments.\n\n* Significant operational experience with deploying, monitoring, and maintaining large-scale A.I. applications in production environments. Not just research and prototypes.\n\n* Solid track record of making effective design decisions balancing near-term and long-term objectives.\n\n* Know when to use commercial or open-source solutions, when to delegate to a teammate, and when to roll up your sleeves and code it yourself.\n\n* Work effectively in agile teams with remote members; get stuff done with minimal guidance and zero BS, help others, and know when to ask for help.\n\n* Clearly communicate complex technical and product issues to non-technical team members, managers, clients, etc. \n\n\nNice-to-haves:\n\n* Advanced degree (MS/PhD) in a quantitative field such as Computer Science or Statistics.\n\n* Proficiency in C++, Python, Scala, or other commonly-used languages.\n\n* Experience with analytics visualization libraries.\n\n* Conversant with relational, column, object, and graph database fundamentals and strong practical experience in any of those paradigms.\n\n* Deep understanding of how to build software agents and conversational workflows.\n\n* Knowledge of capital markets concepts, entities, and processes.\n\n\nOur stack:\n\n* Java, C++, Python, JavaScript/ECMAscript + Node, Angular, Electron, Scala, etc.\n\n* A variety of open source and in-house frameworks for natural language processing and machine learning including artificial neural networks / deep learning.\n\n* Hybrid of AWS (EC2, S3, RDS, R53) + dedicated datacenter network, server and GPU/coprocessor infrastructure.\n\n* Cassandra, Aurora plus in-house streaming analytics pipeline (similar to Apache Flink) and indexing/query engine (similar to ElasticSearch).\n\n* In-house messaging frameworks for low-latency (sub-microsecond sensitivity) multicast and global-scale TCP (similarities to protobufs/FixFast/zeromq/itch).\n\n* Ansible, Git, Subversion, PagerDuty, Icinga, Grafana, Observium, LDAP, Jenkins, Maven, Purify, VisualVM, Wireshark, Eclipse, IntelliJ.\n\nThis position offers a great opportunity to work with advanced technologies, collaborate with a top-notch, global team, and disrupt a highly visible, multi-billion-dollar market. \n\n\n\nCompensation:\n\nWe understand how to attract and retain the best talent and offer a competitive mix of salary, benefits and equity. We also understand how important it is for you to feel challenged, to have opportunities to learn new things, to have the flexibility to balance your work and personal life, and to know that your work has impact in the real world.\n\nWe have team members on four continents and we're adept at making remote workers feel like part of the team. If you join our NYC main office be sure to bring your Nerf toys, your drones and your maker gear - we’re into that stuff, too.\n\n\n\nInterview Process:\n\nIf you can see yourself at Selerity, send your resume and/or online profile (e.g. LinkedIn) to [email protected]. We’ll arrange a short introductory phone call and if it sounds like there’s a match we'll arrange for you to meet the team for a full interview. \n\nThe interview process lasts several hours and is sometimes split across two days on site, or about two weeks with remote interviews. It is intended to be challenging - but the developers you meet and the topics you’ll be asked to explain (and code!) should give you a clear sense of what it would be like to work at Selerity. \n\nWe value different perspectives and have built a team that reflects that diversity while maintaining the highest standards of excellence. You can rest assured that we welcome talented engineers regardless of their age, gender, sexual orientation, religion, ethnicity or national origin.\n\n\n\n\n\nRecruiters: Please note that we are not currently accepting referrals from recruiters for this position. \n\n#Salary and compensation\n
No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Senior, Engineer, Finance, Java, Apache and Linux jobs that are similar:\n\n
$70,000 — $120,000/year\n
\n\n#Benefits\n
๐ฐ 401(k)\n\n๐ Distributed team\n\nโฐ Async\n\n๐ค Vision insurance\n\n๐ฆท Dental insurance\n\n๐ Medical insurance\n\n๐ Unlimited vacation\n\n๐ Paid time off\n\n๐ 4 day workweek\n\n๐ฐ 401k matching\n\n๐ Company retreats\n\n๐ฌ Coworking budget\n\n๐ Learning budget\n\n๐ช Free gym membership\n\n๐ง Mental wellness budget\n\n๐ฅ Home office budget\n\n๐ฅง Pay in crypto\n\n๐ฅธ Pseudonymous\n\n๐ฐ Profit sharing\n\n๐ฐ Equity compensation\n\nโฌ๏ธ No whiteboard interview\n\n๐ No monitoring system\n\n๐ซ No politics at work\n\n๐ We hire old (and young)\n\n
# How do you apply?\n\nThis job post has been closed by the poster, which means they probably have enough applicants now. Please do not apply.
This job post is closed and the position is probably filled. Please do not apply. Work for Doximity and want to re-open this job? Use the edit link in the email when you posted the job!
Why work at Doximity?\n\nDoximity is the leading social network for healthcare professionals with over 70% of U.S. doctors as members. We have strong revenues, real market traction, and we're putting a dent in the inefficiencies of our $2.5 trillion U.S. healthcare system. After the iPhone, Doximity is the fastest adopted product by doctors of all time. Our founder, Jeff Tangney, is the founder & former President and COO of Epocrates (IPO in 2010), and Nate Gross is the founder of digital health accelerator RockHealth. Our investors include top venture capital firms who've invested in Box, Salesforce, Skype, SpaceX, Tesla Motors, Twitter, Tumblr, Mulesoft, and Yammer. Our beautiful offices are located in SoMa San Francisco.\n\nSkills & Requirements\n\n-3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred.\n-3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines.\n-Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases.\n-Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data.\n-Solid understanding of the foundational concepts of machine learning and artificial intelligence.\n-A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies.\n-2+ years of experience using version control, especially Git.\n-Familiarity with Linux, AWS, Redshift.\n-Deep learning experience preferred.\n-Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\nWhat you can expect\n\n-Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact.\n-Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximityโs products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximityโs data science platform.\n-Improve the accuracy, runtime, scalability and reliability of machine intelligence systems\n-Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial.\n\nTechnical Stack\n\n-We historically favor Python and MySQL (SQLAlchemy), but leverage other tools when appropriate for the job at hand.\n-Machine learning (linear/logistic regression, ensemble models, boosted models, deep learning models, clustering, NLP, text categorization, user modeling, collaborative filtering, topic modeling, etc) via industry-standard packages (sklearn, Keras, NLTK, Spark ML/MLlib, GraphX/GraphFrames, NetworkX, gensim).\n-A dedicated cluster is maintained to run Apache Spark for computationally intensive tasks.\n-Storage solutions: Percona, Redshift, S3, HDFS, Hive, Neo4j, and Elasticsearch.\n-Computational resources: EC2, Spark.\n-Workflow management: Airflow.\n\nFun facts about the Data Science team\n\n-We have one of the richest healthcare datasets in the world.\n-We build code that addresses user needs, solves business problems, and streamlines internal processes.\n-The members of our team bring a diverse set of technical and cultural backgrounds.\n-Business decisions at Doximity are driven by our data, analyses, and insights.\n-Hundreds of thousands of healthcare professionals will utilize the products you build.\n-A couple times a year we run a co-op where you can pick a few people you'd like to work with and drive a specific company goal.\n-We like to have fun - company outings, team lunches, and happy hours! \n\nPlease mention the words **WAVE SPOT WORTH** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xNzE=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n
No salary data published by company so we estimated salary based on similar jobs related to Git, Python, Machine Learning, Data Science, Engineer, Linux, Docker and Apache jobs that are similar:\n\n
$80,000 — $122,500/year\n
# How do you apply?\n\nThis job post has been closed by the poster, which means they probably have enough applicants now. Please do not apply.