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!
Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare. Our engineering team is deliberate and self-reflective about the kind of team and culture that we are building, seeking engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth.\n\nOur team brings a diverse set of technical and cultural backgrounds and we like to think pragmatically in choosing the tools most appropriate for the job at hand. We deploy our applications to production on average 50 times per day and have over 350 private repositories in Github, ranging from forks of gems, our own internal gems as well as auxiliary applications. Check out more on the Doximity engineering blog. \n\n**How you’ll make an impact:**\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 Doximity’s products.\n* Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s 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\n**What we’re looking for:**\n* 5+ 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* 3+ years of experience using version control, especially Git.\n* Familiarity with Linux and AWS.\n* Deep learning experience preferred.\n* Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\n**About Doximity**\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\n*Doximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.* \n\nPlease mention the words **MANAGE GAS SPREAD** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xNDg=). 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 Machine Learning, Engineer, Medical and Linux jobs that are similar:\n\n
$75,000 — $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.
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!
Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare. Our engineering team is deliberate and self-reflective about the kind of team and culture that we are building, seeking engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth.\n\nOur team brings a diverse set of technical and cultural backgrounds and we like to think pragmatically in choosing the tools most appropriate for the job at hand. We deploy our applications to production on average 50 times per day and have over 350 private repositories in Github, ranging from forks of gems, our own internal gems as well as auxiliary applications. Check out more on the Doximity engineering blog. \n\n**How you’ll make an impact:**\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 Doximity’s products.\n* Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s 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\n**What we’re looking for:**\n\n* 5+ 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* 3+ years of experience using version control, especially Git.\n* Familiarity with Linux and AWS.\n* Deep learning experience preferred.\n* Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\n**About Doximity**\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\n*Doximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.* \n\n# Requirements\nUse apply button \n\nPlease mention the words **BOIL HOOD GENTLE** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xNDg=). 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 Machine Learning, Data Science, Engineer, Medical and Linux jobs that are similar:\n\n
$80,000 — $125,000/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.
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!
Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare.\n\nHow you’ll make an impact:\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 Doximity’s products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s 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\nWhat we’re looking for:\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\nAbout Doximity\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\nDoximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. \n\nPlease mention the words **BARELY INVOLVE INNER** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xNDg=). 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, Engineer, Linux and Medical jobs that are similar:\n\n
$75,000 — $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.
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 Doximity’s products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s 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 (#RMjE2LjczLjIxNi4xNDg=). 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.
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