[Hiring] AI/ML Scientist @Helix

Role Description

At Helix, our mission is simple: to help everyone improve their lives through their DNA. Ready to make a real-world impact with your skills? At Helix, we're transforming healthcare by making genomics a standard of care. We partner with health systems and life science companies to accelerate the integration of genomic data into clinical practice.

Helix maintains one of the largest linked genomic and clinical datasets in the United States. Helix's Data Science & AI team innovates and develops state-of-the-art models that leverage this clinicogenomic dataset to better understand and predict a patient's journey, taking precision medicine to a new level.

Work you would touch in the first year:

• Training and evaluating generative models on longitudinal clinical records fused with variant-level germline genomics, to forecast disease onset and patient trajectory.
• Building and measuring LLM agentic solutions that pull structured findings out of clinical text and the published literature.
• Contributing to our multi-agent pipeline for clinical variant interpretation, which is in production today and used by our clinical genomics team on every uncurated variant.
• Feature and representation work on genomic data: turning variant and gene-level information into something a model can actually use.
• Running experiments carefully enough to ensure we can trust the results, which primarily means designing the comparison correctly before launching the job.

As an AI/ML Scientist, you will:

• Own well-scoped pieces of a larger modeling effort: implement, train, evaluate, and report.
• Write experiment code that colleagues on the team can read, rerun, and trust.
• Build and maintain evaluation pipelines, and be honest about what they do and do not measure.
• Investigate data quality issues, as they are a necessity in healthcare data.
• Present your results to the team and leadership, including the ones that did not work.
• Collaborate as the AI/ML voice across bioinformatics, clinical, and engineering stakeholders.
• Draft scientific writeups and internal summaries of the team's findings, and carry results through to papers or conference presentations.

Qualifications

• MS or PhD in machine learning, computer science, statistics, computational biology, bioinformatics, or a related quantitative field, or equivalent experience.
• 2 to 5 years of applied machine learning experience beyond your degree. Strong PhD work counts.
• Solid Python skills.
• Comfortable with practical parts: git, containers, running jobs on cloud GPUs, tracking experiments.
• Working knowledge of statistics.
• Genuine interest in biology and the clinical problem.
• Comfortable saying "I do not know yet."

Requirements

• Any exposure to healthcare, genomics, or proteomics data: EHRs, claims, sequencing, imaging, registries.
• Coursework or projects in computational biology, statistical genetics, or biomedical NLP.
• Experience with LLM APIs, fine-tuning, or agent frameworks.
• Experience with large-scale data tooling (Spark, Dask, Ray, or similar) or with SQL on genuinely large tables.
• Familiarity with healthcare data standards (OMOP/CDM).
• Familiarity with variant interpretation and classification guidelines (ACMG/AMP) or clinical genetics more broadly.
• Public code, a paper, or a technical writeup.
• Experience with PyTorch, Lightning, AWS SageMaker.

Benefits

• Comprehensive Health Insurance with Date of Hire eligibility.
• 12 weeks Helix Paid Parental Leave option.
• Comprehensive Well-Being Benefits.
• Flexible PTO.
• Remote options for many roles and a home office stipend.

Expected Interview Process

• Recruiter Screen
• Manager Screen
• Tech Screens
• Final Loop
• Offer

Expected Pay For This Role

• Expected Helix Base: $97,000 - $122,500.
• Expected Helix Discretionary Annual Bonus: 10% of your annual salary.
• Equity: We offer generous equity at Helix.

What To Expect During Your First 90 days

• First 30 days: learning the Helix way, completing training and onboarding, and getting introduced to your team and relevant stakeholders.
• Day 30 - 60: contributing to projects and developing a deeper understanding of Helix’s products, services, and capabilities.
• Day 60 - 90: building your OKRs with your manager and taking ownership of projects and initiatives on your team.