Opportunity Overview:
As a Lead Machine Learning Engineer, you’ll join our growing team of world-class machine learning engineers and clinical experts to deploy machine learning models that help automate burdensome administrative clinical practices.
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.
What you’ll do:
- Design, develop and deploy advanced machine learning algorithms for retrieval, classification and generative use cases.
- Develop reliable and scalable production machine learning systems.
- Write and maintain reusable codebases to perform data preprocessing, model training, evaluation, and deployment
- Provide software and machine learning best practice guidance to junior engineers
- Work cross-functionally with diverse stakeholders, including product managers, clinicians, and technical leadership to align ML solutions with Cohere’s core objectives.
ISMS roles and responsibilities:
- Good knowledge of Information practices.
- Assist the manager in all the information security activities implementation and maintenance process.
- Ensuring the team and imparted with Competence related to Information security
- Responsible for implementation of security policies and procedures and report any issues to the Information Security Manager.
Required Qualifications:
Must-haves
- Minimum 7+ years of experience in applied ML with a masters degree or 5+ years with a PhD, ideally in a senior or lead role in a large technology or healthcare company
- Clear understanding of model building, model maintenance and the measures that optimize models for production use
- Understand experimental design and can independently perform collection, measurement, and interpretation of results
- Expert in Python with experience in deep learning frameworks (e.g., PyTorch)
- Hands on experience building deep learning models (e.g., transformers) for NLP tasks
- MS or PhD required
Nice-to-haves
- Experience with generative AI or Retrieval Augmented Generation (RAG)
- Experience working with unstructured healthcare data (e.g., clinical notes)
- Experience with OCR or image-based document understanding techniques
- Hands on experience using AWS tools such as SageMaker Studio
Interview Process*:
- Connect with Talent Acquisition
- Meet with the Hiring Manager
- Behavioral Interview(s)
- Case Study
- Interview with Senior Leadership
*Subject to change
About Cohere Health:
Cohere Health’s clinical intelligence platform and agentic AI-powered solutions connect health plans’ strategic goals and providers’ needs, optimizing the speed, cost, and quality of care. With an enterprise approach that streamlines payer-provider decision-making across the care continuum–including policy, prior authorization, payment accuracy, and more–the company improves collaboration and reduces burden, resulting in up to 8x ROI and 94% provider satisfaction.
With the acquisition of ZignaAI, we expanded our AI-native platform with a comprehensive Payment Integrity Suite that spans data mining, clinical and coding validation, authorization and claims reconciliation, and end-to-end payment integrity services across pre- and post-pay workflows. By connecting clinical and payment insights, our transparent, AI-powered solutions help health plans proactively improve payment accuracy, reduce waste and vendor dependency, strengthen provider relationships, and build smarter, more efficient payment integrity programs.
Cohere Health’s innovations continue to receive industry-wide recognition. We’ve been recognized on TIME’s World Top HealthTech Companies 2025 list, the 2025 Inc. 5000 list, in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024.
We can’t wait to learn more about you and meet you at Cohere Health!
Equal Opportunity Statement:
Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.
