ML Engineer II: Build & Optimize Value-Driven ML Models

JOB SUMMARY
The ML Engineer II will design and develop ML models that deliver accurate results to solve identified business problems using state-of-the-art techniques, under the guidance of Senior ML Engineers. This role involves collaborating with cross-functional teams to build valuable ML solutions for products.

Key Responsibilities

• Work with cross-functional teams (business, technology, product) to understand product vision and build ML solutions that bring value to the product.

• Execute data wrangling activities to create viable datasets for ML problems.

• Conduct ML experiments to assess feasibility and build baseline models.

• Fine-tune baseline models for optimum performance.

• Test models internally against business acceptance criteria.

• Identify areas and techniques for model optimization based on test results.

• Document relevant artifacts for business communication.

• Collaborate with data scientists on model deployment.

• Work with product teams in planning and execution of new product releases.

• Set OKRs and success steps, and provide feedback on goals for team members.

Required Qualifications

• Ability to design and develop ML models to solve business problems using state-of-the-art techniques under guidance.

• Experience working with cross-functional teams including business, technology, and product.

• Proficiency in data wrangling activities to create viable datasets.

• Experience conducting ML experiments to understand feasibility and build baseline models.

• Experience fine-tuning models for optimum performance.

• Experience testing models internally per acceptance criteria.

• Ability to identify areas and techniques for model optimization.

• Experience documenting relevant artifacts for business communication.

• Experience collaborating with data scientists for model deployment.

• Experience working with product teams in planning and execution.

• Experience setting OKRs and success steps, and providing feedback on team goals.

Notes:

Mandatory areas – ML Engineer – Prompt engineer

Must Have skills:

• Chain-of-thought

Mandatory, if Applicable

Domain Experience (If any) – Healthcare good to have.

Must have Certifications – NA

If yes, provide dates, details of account/project

Location:

Onsite Requirement – Hybrid

Number of days onsite – NA

If onsite, provide Office Address – Connecticut-USA