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Staff Machine Learning Engineer

AT CVS Health
CVS Health

Staff Machine Learning Engineer

New York, NY

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand - with heart at its center - our purpose sends a personal message that how we deliver our services is just as important as what we deliver.

Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable. Our Mission: We are seeking a talented and experienced Machine Learning Engineer to join our team. You will play a crucial role in developing and implementing innovative machine learning solutions, leveraging Google Cloud Platform and Vertex AI Workbench to drive business success and solve complex challenges. Responsibilities: Develop and Lead MLOps Solutions:

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  • Define and implement machine learning operations solutions that align with business goals and deliver measurable value.
  • Identify key business problems and opportunities where machine learning can be applied effectively.
  • Prioritize and select projects that align with long-term business goals.
Design and Build MLOps Pipelines:
  • Architect and develop reusable MLOps pipelines using GCP and Vertex AI Workbench.
  • Ensure these pipelines are scalable, maintainable, and adhere to best practices.
  • Oversee the implementation of these pipelines in a production-ready environment for use by operational teams across the enterprise.
  • Collaborate with different IT and business leaders to define machine learning product roadmaps.
Collaboration and Communication:
  • Work closely with infrastructure, governance, security, and business leaders to ensure alignment between the MLOps strategy and overall business objectives .
  • Effectively communicate the value proposition and technical complexities of machine learning projects to diverse stakeholders.
  • Advocate for responsible AI practices and ensure adherence to ethical guidelines and regulations.
Qualifications:
  • 7 + years of experience in machine learning engineering with strong technical expertise in MLOps , GCP, and Vertex AI Workbench.
  • Bachelor's degree in Computer Science , Machine Learning, or a related field is required ; a Master's degree or PhD is preferred.
  • Proven track record of successfully designing, building, and deploying machine learning solutions that deliver business impact.
  • Experience with cloud-based deployment methodologies and familiarity with cloud-agnostic approaches.
  • Exceptional leadership and communication skills, with the ability to inspire, motivate, and mentor a team of engineers.
  • Strong collaboration and interpersonal skills, capable of building bridges and fostering communication across diverse teams.
Core Skills: Leadership and Business Acumen:
  • Business Innovation and Strategy
  • Leading Teams and People Development
  • Business Problem-Solving and Managing Relationships
Advanced Analytics Modeling:
  • Developing & Applying Algorithms (Python, R)
  • Machine Learning (TensorFlow, PyTorch , Scikit-learn)
  • Programming Languages (Model Development) (Python, R, Java)
  • Reinforcement Learning & Deep Learning ( Keras , TensorFlow)
  • Simulation & Optimization ( SimPy , OptaPlanner )
Analytics Deployment:
  • Machine Learning Operations (Vertex AI, Kubeflow)
  • Solution Implementation (CI/CD, Docker, Kubernetes)
  • Solution Maintenance ( MLflow , TFX)
Data Delivery:
  • Business Logic Implementation (SQL, NoSQL)
  • Data Integration (Apache Kafka, Apache NiFi )
  • Data Modeling ( BigQuery , Dataflow)
  • Using, Building, & Maintaining Integration Frameworks (Airflow, dbt )
Pay Range

The typical pay range for this role is:$142,140.00 - $284,280.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company's equity award program.

In addition to your compensation, enjoy the rewards of an organization that puts our heart into caring for our colleagues and our communities. The Company offers a full range of medical, dental, and vision benefits. Eligible employees may enroll in the Company's 401(k) retirement savings plan, and an Employee Stock Purchase Plan is also available for eligible employees. The Company provides a fully-paid term life insurance plan to eligible employees, and short-term and long term disability benefits. CVS Health also offers numerous well-being programs, education assistance, free development courses, a CVS store discount, and discount programs with participating partners. As for time off, Company employees enjoy Paid Time Off ("PTO") or vacation pay, as well as paid holidays throughout the calendar year. Number of paid holidays, sick time and other time off are provided consistent with relevant state law and Company policies.

For more detailed information on available benefits, please visit Benefits | CVS HealthWe anticipate the application window for this opening will close on: 02/17/2025Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

Client-provided location(s): New York, NY, USA
Job ID: CVS-R0493344
Employment Type: Other

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • HSA
    • HSA With Employer Contribution
    • Pet Insurance
    • Mental Health Benefits
  • Parental Benefits

    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
  • Financial and Retirement

    • 401(K) With Company Matching
  • Professional Development

    • Tuition Reimbursement
  • Diversity and Inclusion

    • Employee Resource Groups (ERG)
    • Diversity, Equity, and Inclusion Program