gem

AI/ML Scientist

Helix

Remote, CAN

Full-time

Entry · 2+ years experience

Remote

CAD 97000-122500 yearly / year

Discovered 2 days ago

Pythongitcontainerscloud GPUsLLM APIsSpark

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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.
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. In healthcare data, these are not a distraction from modeling work; they are a necessity
Present your results to the team and leadership, including the ones that did not work, and have opportunities to represent the work externally over time
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
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. You can write a training loop, read someone else's, and debug it when the loss goes flat
You get real leverage out of AI tools and coding assistants, and you know when to trust their output and when to check it
Comfortable with the practical parts: git, containers, running jobs on cloud GPUs, tracking experiments
Working knowledge of statistics: you know what a train/test leak is, why a baseline matters, and when a difference between two numbers is not a difference
Genuine interest in biology and the clinical problem. You do not need to arrive knowing genomics, but you do need to want to learn it
You are comfortable saying "I do not know yet"
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, especially where you had to measure whether the thing worked
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: something we can read that shows how you think

• PyTorch, Lightning, AWS SageMaker

Expected Helix Base: $97,000 - $122,500
Expected Helix Discretionary Annual Bonus: 10% of your annual salary
Equity: We offer generous equity at Helix. If you receive a Helix offer your recruiter will book dedicated time with you to educate you on our equity model.
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
First 30 days: you’ll spend time learning the Helix way, completing training and onboarding for your roles, and getting introduced to your team and relevant stakeholders. You’ll also gain a deeper understanding of our customers, our products, the impact we make in the lives of our communities, and how to thrive at Helix through participation in Helix U.
Day 30 - 60: you’ll spend time contributing to projects, deeply familiarizing yourself with team and company processes, and developing a deeper understanding of Helix’s products, services and capabilities.
Day 60 - 90: you’ll build your OKRs with your manager, start to take ownership of projects and initiatives on your team, and begin to demonstrate your impact on the Helix mission.