Principal Machine Learning Operations Engineer
Genentech
Remote job description
The Position
WHO WE ARE
Our Strategic Analytics & Intelligence (SAI) team isn't just deciphering data. We're here to help solve the world's most complex healthcare challenges and improve the lives of patients.
With a mix of competitive intelligence, market research, data science, advanced analytics, access, and forecasting, SAI unlocks key insights for our internal partners that ultimately benefit healthcare providers and patients. Even if you've never worked in biotech, you'll establish yourself as an expert alongside other specialists. Plus, you can gain new experiences across marketing disciplines, therapeutic areas, and commercial operations. The entire time, you'll be surrounded by a diverse and inclusive team that aims to reflect the world we serve.
The Data Science Team within SAI exists to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data quicker and more effectively. As a center of excellence, the DS team has 3 primary remitsOwning Advanced Data Science Strategy and Innovation for SAI and CMG; Application of Data Science to CMG enterprise priorities, and; Driving the Data Science Capability on behalf of the SAI department. The team leverages advanced data science capabilities, working across CMG to develop strategic and holistic solutions by identifying and leading innovative analytic projects & pilots to enable GNE to deliver for our customers.
What We Are Looking For
We are looking for a seasoned Principal Machine Learning (ML) Operations Engineer to lead our ML lifecycle capability which includes model training, deployment and monitoring. Reporting to the Senior Director of Data Science team, the Principal of ML Engineering & Operations will actively participate in the ideation, the design and the prototyping of ML powered products as part of Genentech's digital transformation. We are looking for a leader who will:
* Work cross-functionally and collaboratively to foster MLOps and ML Engineering best practices across the organization
* Influence other leaders and challenge the status quo
* Own and implement the MLOps roadmap for CMG DS team in collaboration with IT
* Keep the organization up to date on the best in class MLOps technologies
* Position location is South San Francisco, but remote work options will be considered. Relocation benefits are available for this job posting.
Key Responsibilities
* Own the ML Engineering and Operations roadmap from conception to execution in terms of tools, systems, best practices and processes across the organization.
* Work closely with the IT department in order to design, build, manage and monitor the machine learning infrastructure in multi-modal settings (text, audio..) for the CMG Data Science team.
* Optimize AI/ML production release and deployment process. Establish scalable, efficient, and automated processes for large scale ML model deployments.
* Deploy novel and cutting edge deep learning (e.g NLP) models at scale
* Develop systems, tools, and processes to monitor ML models in production, monitoring drift and performance and initiating retraining and validation as necessary.
* Develop systems, tools, and processes to govern ML models for compliance, technical debt, versioning, traceability and auditability.
* Write high quality code that has high test coverage and actively participate in code reviews to help improve code quality.
* Actively participate in data science experimentations and prototyping efforts, evaluate and support ML models production and scale to enterprise level.
* Produce clear and readable documentation about code deployment and model monitoring frameworks as well as project operations.
* Communicate progress to technical and non-technical stakeholders across CMG and SAI organizations.
* Work in an agile environment based on the defined sprint backlogs to deliver the assigned work in the stipulated timelines.
* Work closely with IT to stay up-to-date on upcoming changes and upgrades to Genentech's infrastructure.
Requirements
* A bachelor's, master's, or doctorate degree in Computer Engineering or Computer Science , and a minimum of 10 years of machine learning and data science working experience.
* Proven and extensive work experience with ML platforms and cloud based frameworks.
* Good understanding of ML and AI concepts and hands-on experience in ML model development.
* Proven professional experience deploying ML models using Kubernetes, AWS, Docker.
* Strong experience in Python, SQL Databases, NoSQL databases (e.g. druid), data lakes (e.g. snowflake), data modeling, data ingestion, CI/CD frameworks (e.g. CircleCI, Jenkins), containerization (e.g. Docker), orchestration (e.g. Kubernetes), and workflow scheduling (e.g. airflow) technologies.
* Experience in data wrangling in python using NumPy, pandas, dask, etc.
* Ability to navigate in a cross-functional environment with appropriate agile based approaches for sprint planning, backlog grooming, and timelines tracking.
* Proven experience with multitasking, prioritization and time management.
* Preferred experience building and optimizing structured and unstructured big data pipelines, architectures, and datasets.
* Impeccable verbal and written communication skills with the ability to translate complex concepts into simple easy to understand content for non technical audience.
* Proven ability to work independently and take calculated risks to fail fast.
Our Operating Principles
Put Patients First : I always act as if patients I know are in the room and do what's best for them.
Follow the science : I seek answers through experiments, data and debate, and act on facts.
Act as one team : I care, collaborate and commit without boundaries, and trust others to do their part.
Embrace differences : I seek diverse perspectives, invite opposing views, and challenge myself and others.
Accelerate learning : I push to learn new things even if difficult, and openly share my successes and failures.
Simplify radically : I eliminate complexity, reuse with pride, and accomplish more with less.
Make impact now : I take accountability to do what's right, deliver value fast, and don't wait for certainty.
Think long term : I choose actions today that benefit future generations.
For Colorado-based applicants, the expected salary range for this position is $192,870 to $225,015. Actual pay will be determined based on experience, qualifications, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
This position also qualifies for the benefits listed below.
Roche offers highly competitive benefit plans and programs, including:
?Medical, dental and vision insurance
?401(k) and 401(k) matching
?Paid time off
?Roche Long Term Incentive Plan (available at certain position levels)
#LI-Remote
#SAIData
#LI-NN2
Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
Genentech requires all new hires to be fully vaccinated against COVID-19 as of their start date. This requirement is a condition of employment at Genentech, and it applies regardless of whether the position is located at a Genentech campus or is fully remote. If you are unable to receive the vaccine due to a disability or serious medical condition, or because it is prohibited as a result of your sincerely held religious beliefs, you will have an opportunity to request a reasonable accommodation.
Job Facts
JOB FUNCTION
COMPANY/DIVISION
Genentech SCHEDULE
JOB TYPE
Full time
Summary
Company name: Genentech
Remote job title: Principal Machine Learning Operations Engineer
WHO WE ARE
Our Strategic Analytics & Intelligence (SAI) team isn't just deciphering data. We're here to help solve the world's most complex healthcare challenges and improve the lives of patients.
With a mix of competitive intelligence, market research, data science, advanced analytics, access, and forecasting, SAI unlocks key insights for our internal partners that ultimately benefit healthcare providers and patients. Even if you've never worked in biotech, you'll establish yourself as an expert alongside other specialists. Plus, you can gain new experiences across marketing disciplines, therapeutic areas, and commercial operations. The entire time, you'll be surrounded by a diverse and inclusive team that aims to reflect the world we serve.
The Data Science Team within SAI exists to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data quicker and more effectively. As a center of excellence, the DS team has 3 primary remitsOwning Advanced Data Science Strategy and Innovation for SAI and CMG; Application of Data Science to CMG enterprise priorities, and; Driving the Data Science Capability on behalf of the SAI department. The team leverages advanced data science capabilities, working across CMG to develop strategic and holistic solutions by identifying and leading innovative analytic projects & pilots to enable GNE to deliver for our customers.
What We Are Looking For
We are looking for a seasoned Principal Machine Learning (ML) Operations Engineer to lead our ML lifecycle capability which includes model training, deployment and monitoring. Reporting to the Senior Director of Data Science team, the Principal of ML Engineering & Operations will actively participate in the ideation, the design and the prototyping of ML powered products as part of Genentech's digital transformation. We are looking for a leader who will:
* Work cross-functionally and collaboratively to foster MLOps and ML Engineering best practices across the organization
* Influence other leaders and challenge the status quo
* Own and implement the MLOps roadmap for CMG DS team in collaboration with IT
* Keep the organization up to date on the best in class MLOps technologies
* Position location is South San Francisco, but remote work options will be considered. Relocation benefits are available for this job posting.
Key Responsibilities
* Own the ML Engineering and Operations roadmap from conception to execution in terms of tools, systems, best practices and processes across the organization.
* Work closely with the IT department in order to design, build, manage and monitor the machine learning infrastructure in multi-modal settings (text, audio..) for the CMG Data Science team.
* Optimize AI/ML production release and deployment process. Establish scalable, efficient, and automated processes for large scale ML model deployments.
* Deploy novel and cutting edge deep learning (e.g NLP) models at scale
* Develop systems, tools, and processes to monitor ML models in production, monitoring drift and performance and initiating retraining and validation as necessary.
* Develop systems, tools, and processes to govern ML models for compliance, technical debt, versioning, traceability and auditability.
* Write high quality code that has high test coverage and actively participate in code reviews to help improve code quality.
* Actively participate in data science experimentations and prototyping efforts, evaluate and support ML models production and scale to enterprise level.
* Produce clear and readable documentation about code deployment and model monitoring frameworks as well as project operations.
* Communicate progress to technical and non-technical stakeholders across CMG and SAI organizations.
* Work in an agile environment based on the defined sprint backlogs to deliver the assigned work in the stipulated timelines.
* Work closely with IT to stay up-to-date on upcoming changes and upgrades to Genentech's infrastructure.
Requirements
* A bachelor's, master's, or doctorate degree in Computer Engineering or Computer Science , and a minimum of 10 years of machine learning and data science working experience.
* Proven and extensive work experience with ML platforms and cloud based frameworks.
* Good understanding of ML and AI concepts and hands-on experience in ML model development.
* Proven professional experience deploying ML models using Kubernetes, AWS, Docker.
* Strong experience in Python, SQL Databases, NoSQL databases (e.g. druid), data lakes (e.g. snowflake), data modeling, data ingestion, CI/CD frameworks (e.g. CircleCI, Jenkins), containerization (e.g. Docker), orchestration (e.g. Kubernetes), and workflow scheduling (e.g. airflow) technologies.
* Experience in data wrangling in python using NumPy, pandas, dask, etc.
* Ability to navigate in a cross-functional environment with appropriate agile based approaches for sprint planning, backlog grooming, and timelines tracking.
* Proven experience with multitasking, prioritization and time management.
* Preferred experience building and optimizing structured and unstructured big data pipelines, architectures, and datasets.
* Impeccable verbal and written communication skills with the ability to translate complex concepts into simple easy to understand content for non technical audience.
* Proven ability to work independently and take calculated risks to fail fast.
Our Operating Principles
Put Patients First : I always act as if patients I know are in the room and do what's best for them.
Follow the science : I seek answers through experiments, data and debate, and act on facts.
Act as one team : I care, collaborate and commit without boundaries, and trust others to do their part.
Embrace differences : I seek diverse perspectives, invite opposing views, and challenge myself and others.
Accelerate learning : I push to learn new things even if difficult, and openly share my successes and failures.
Simplify radically : I eliminate complexity, reuse with pride, and accomplish more with less.
Make impact now : I take accountability to do what's right, deliver value fast, and don't wait for certainty.
Think long term : I choose actions today that benefit future generations.
For Colorado-based applicants, the expected salary range for this position is $192,870 to $225,015. Actual pay will be determined based on experience, qualifications, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
This position also qualifies for the benefits listed below.
Roche offers highly competitive benefit plans and programs, including:
?Medical, dental and vision insurance
?401(k) and 401(k) matching
?Paid time off
?Roche Long Term Incentive Plan (available at certain position levels)
#LI-Remote
#SAIData
#LI-NN2
Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
Genentech requires all new hires to be fully vaccinated against COVID-19 as of their start date. This requirement is a condition of employment at Genentech, and it applies regardless of whether the position is located at a Genentech campus or is fully remote. If you are unable to receive the vaccine due to a disability or serious medical condition, or because it is prohibited as a result of your sincerely held religious beliefs, you will have an opportunity to request a reasonable accommodation.
Job Facts
JOB FUNCTION
COMPANY/DIVISION
Genentech SCHEDULE
JOB TYPE
Full time
Summary
Company name: Genentech
Remote job title: Principal Machine Learning Operations Engineer
-
location or timezone
-
category
Software Development -
posted
691 days ago
United Stateshttps://www.remote.io/remote-software-development-jobs/principal-machine-learning-operations-engineer-30932