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Machine Learning Engineer ll

Job in Philadelphia, Philadelphia County, Pennsylvania, 19113, USA
Listing for: Cohere Health
Full Time position
Listed on 2026-10-30
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 140000 USD Yearly USD 120000.00 140000.00 YEAR
Job Description & How to Apply Below
Opportunity Overview

We are looking for a Machine Learning Engineer ii to join our team! Our ML team's work is focused on designing, deploying, and monitoring production models which extract or predict relevant clinical findings from structured and unstructured data sources. In this role, you'll join our growing team of world-class engineers, statisticians, and clinical experts to deploy machine learning algorithms that help automate burdensome administrative clinical practices.

You will be tasked with finding the most promising opportunities for impact and then delivering on them. This is a unique opportunity to join a high caliber engineering team that is growing quickly. You will build impactful healthcare technology on a modern tech stack.

What you’ll do:
  • Perform in-depth analysis of healthcare data to independently design, develop, and deliver clinical ML models.
  • Build reliable and scalable production machine learning systems.
  • Work on feature engineering, statistical analysis, developing novel ML techniques, understanding performance, and improving model run time.
  • Work cross-functionally across diverse stakeholders, including product managers, statisticians, clinicians, and clinical analysts.
What you’ll need:
  • You have 2-4 years full time professional experience in Machine Learning.
  • You have an MS in computer science, machine learning, computational linguistics, statistics, mathematics or similar field.
  • You have hands on experience building with modern language models, including context-engineering LLMs or fine-tuning SLMs.
  • You understand scientific best practice in experimental design and can independently perform data collection, measurement, and interpretation of results.
  • You have experience configuring, training, evaluating, deploying, and maintaining models in a production setting.
  • Advanced proficiency in Python and familiarity with ML frameworks such as PyTorch.
Pay & Perks:
  • Fully remote opportunity with about 5% travel
  • Medical, dental, vision, life, disability insurance, and Employee Assistance Program
  • 401K retirement plan with company match; flexible spending and health savings account
  • Up to 184 hours (23 days) of PTO per year + company holidays
  • Up to 14 weeks of paid parental leave
  • Pet insurance
  • The salary range for this position is $120,000 - $140,000 annually; as part of a total benefits package which includes health insurance, 401k and bonus. In accordance with state applicable laws, Cohere is required to provide a reasonable estimate of the compensation range for this role. Individual pay decisions are ultimately based on a number of factors, including but not limited to qualifications for the role, experience level, skillset, and internal alignment.
Interview

Process:
  • Connect with Talent Acquisition for a Preliminary Phone Screening
  • Meet your Hiring Manager!
  • Behavioral Interview(s)
  • Live Coding
  • Case Study
  • Subject to change
About Cohere Health:

Cohere Health's clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members. With the acquisition of ZignaAI, we've further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate, an AI-driven clinical and coding validation solution that operates in near real-time.

By unifying pre-service authorization data with post-service claims validation, we're creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures…

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