Position: ML Team Lead

Job Title: Team Lead, ML Eng team – Healthcare AI

Location: Hybrid (Tel Aviv)

Company: Pheno.AI

About Pheno.AI

Pheno.AI is transforming healthcare by building foundation models tailored for biomedical and clinical data. We are developing cutting-edge AI technologies to extract insights from multimodal health data and drive breakthroughs in personalized medicine. Our team combines deep technical expertise with a strong mission-driven mindset.

Who We’re Looking For

We’re looking for a hands-on Team Lead to lead our ML team . You will lead the development of state-of-the-art machine learning algorithms focused on healthcare, clinical, and genomic data. This is a unique opportunity to define and shape the data science roadmap while remaining deeply involved in the research and implementation process.

What You’ll Do

• Lead a team of engineering and data scientists developing cutting edge ML models for healthcare and life science data.
• Design and implement machine learning and deep learning models, from research to production.
• Collaborate cross-functionally with product, data engineering, and software teams.
• Mentor team members and drive technical excellence and innovation within the team.
• Translate complex data into actionable insights that inform clinical and scientific decisions.
• Build scalable pipelines and infrastructure to support high-performance data science workloads.

What You’ll Bring

• B.Sc./M.Sc. or Ph.D. in Computer Science, Statistics, Biomedical Informatics, or a related field
• 5+ years of hands-on experience in machine learning and data science
• 2+ years of experience leading data science or applied ML teams
• Strong Python skills and deep experience with ML libraries such as scikit-learn, PyTorch, TensorFlow, Pandas, etc.
• Proven ability to take ML solutions from concept to production, including model deployment, scaling, monitoring, and lifecycle management
• Solid software engineering practices, including version control (Git), CI/CD, testing frameworks, and code reviews
• Experience designing and building robust data pipelines and ML infrastructure using tools like Airflow, MLflow, or Kubeflow
• Familiarity with cloud platforms (AWS, GCP, or Azure), including services like S3, SageMaker, EC2, Lambda, and container orchestration with Docker/Kubernetes
• Experience working with biomedical, clinical, or genomic data – a major plus
• Strong communication and collaboration skills, with the ability to work cross-functionally with product, engineering, and clinical teams

Bonus Points

• Experience with foundation models, LLMs, and generative AI in a biomedical context.
• Familiarity with data engineering practices and tools (e.g., Spark, Airflow, SQL, etc.).
• Experience with cloud-based ML workflows (e.g., AWS, SageMaker, Databricks ,Vertex AI).
• Experience working in startups or fast-paced R&D environments.

Why Join Us

• Help build AI that will impact the future of healthcare.
• Be part of a mission-driven, interdisciplinary team solving real-world problems.