Is the AI/ML Scientist position at Helix fully remote?

Yes, this AI/ML Scientist position at Helix is a remote position. The role is available for candidates in Canada.

Is this a full-time or part-time AI/ML Scientist role?

This is a full-time AI/ML Scientist position at Helix.

What benefits does Helix offer for this position?

Helix offers the following benefits: Health Insurance, Parental Leave.

What is the salary range for the AI/ML Scientist position?

The salary range for this AI/ML Scientist role is $97k - $122.5k.

How do I apply for the AI/ML Scientist position at Helix?

You can apply for this AI/ML Scientist position by clicking the "Apply Now" button on this page, which will take you to Helix's application portal.

AI/ML Scientist at Helix

Canada

$97k - $122.5k

<div><strong style="background-color: transparent;">Who We Are & What We Do </strong></div><div><span style="background-color: transparent;">At Helix, our mission is simple: to help everyone improve their lives through their DNA.</span></div><div><br></div><div><span style="color: rgb(31, 31, 31);">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. Join us in building a future where healthcare is personalized, proactive, and powered by genomics.</span><span style="background-color: transparent;"> </span></div><div><br></div><div><strong style="background-color: transparent; color: rgb(0, 0, 0);">What is special about this role?</strong></div><div><br></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">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, for example, germline genomes linked to longitudinal clinical records, to better understand and predict a patient's journey, taking precision medicine to a new level.</span></div><div><br></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">You will take ownership of impactful work early on; your results will be influential, and you will collaborate closely with domain experts. You will have direct access to data that most professionals in this field only read about, along with the opportunity to develop a deep understanding of genomic and clinical data alongside senior experts who have dedicated their careers to this work.</span></div><div><br></div><div><strong style="background-color: transparent; color: rgb(0, 0, 0);">Work you would touch in the first year:</strong></div><div><br></div><ul><li class=""><span style="background-color: transparent;">Training and evaluating generative models on longitudinal clinical records fused with variant-level germline genomics, to forecast disease onset and patient trajectory</span></li><li class=""><span style="background-color: transparent;">Building and measuring LLM agentic solutions that pull structured findings out of clinical text and the published literature</span></li><li class=""><span style="background-color: transparent;">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</span></li><li class=""><span style="background-color: transparent;">Feature and representation work on genomic data: turning variant and gene-level information into something a model can actually use</span></li><li class=""><span style="background-color: transparent;">Running experiments carefully enough to ensure we can trust the results, which primarily means designing the comparison correctly before launching the job.</span></li></ul><div><br></div><div><strong style="background-color: transparent; color: rgb(0, 0, 0);">As an AI/ML Scientist, you will:</strong></div><div><br></div><ul><li class=""><span style="background-color: transparent;">Own well-scoped pieces of a larger modeling effort: implement, train, evaluate, and report</span></li><li class=""><span style="background-color: transparent;">Write experiment code that colleagues on the team can read, rerun, and trust</span></li><li class=""><span style="background-color: transparent;">Build and maintain evaluation pipelines, and be honest about what they do and do not measure</span></li><li class=""><span style="background-color: transparent;">Investigate data quality issues. In healthcare data, these are not a distraction from modeling work; they are a necessity</span></li><li class=""><span style="background-color: transparent;">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</span></li><li class=""><span style="background-color: transparent;">Collaborate as the AI/ML voice across bioinformatics, clinical, and engineering stakeholders</span></li><li class=""><span style="background-color: transparent;">Draft scientific writeups and internal summaries of the team's findings, and carry results through to papers or conference presentations</span></li></ul><div><br></div><div><strong style="background-color: transparent; color: rgb(0, 0, 0);">About you:</strong></div><div><br></div><ul><li class=""><span style="background-color: transparent;">MS or PhD in machine learning, computer science, statistics, computational biology, bioinformatics, or a related quantitative field, or equivalent experience</span></li><li class=""><span style="background-color: transparent;">2 to 5 years of applied machine learning experience beyond your degree. Strong PhD work counts</span></li><li class=""><span style="background-color: transparent;">Solid Python skills. You can write a training loop, read someone else's, and debug it when the loss goes flat</span></li><li class=""><span style="background-color: transparent;">You get real leverage out of AI tools and coding assistants, and you know when to trust their output and when to check it</span></li><li class=""><span style="background-color: transparent;">Comfortable with the practical parts: git, containers, running jobs on cloud GPUs, tracking experiments</span></li><li class=""><span style="background-color: transparent;">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</span></li><li class=""><span style="background-color: transparent;">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</span></li><li class=""><span style="background-color: transparent;">You are comfortable saying "I do not know yet"</span></li></ul><div><br></div><div><strong style="background-color: transparent; color: rgb(0, 0, 0);">Pluses:</strong></div><div><br></div><ul><li class=""><span style="background-color: transparent;">Any exposure to healthcare, genomics, or proteomics data: EHRs, claims, sequencing, imaging, registries</span></li><li class=""><span style="background-color: transparent;">Coursework or projects in computational biology, statistical genetics, or biomedical NLP</span></li><li class=""><span style="background-color: transparent;">Experience with LLM APIs, fine-tuning, or agent frameworks, especially where you had to measure whether the thing worked</span></li><li class=""><span style="background-color: transparent;">Experience with large-scale data tooling (Spark, Dask, Ray, or similar) or with SQL on genuinely large tables</span></li><li class=""><span style="background-color: transparent;">Familiarity with healthcare data standards (OMOP/CDM)</span></li><li class=""><span style="background-color: transparent;">Familiarity with variant interpretation and classification guidelines (ACMG/AMP) or clinical genetics more broadly</span></li><li class=""><span style="background-color: transparent;">Public code, a paper, or a technical writeup: something we can read that shows how you think</span></li><li class=""><span style="background-color: transparent;">PyTorch, Lightning, AWS SageMaker</span></li></ul><div><br></div><div><strong>Expected Interview Process:</strong></div><div>1) Recruiter Screen 2) Manager Screen 3) Tech Screens 4) Final Loop 5) Offer </div><div><br></div><div>Expected Pay For This Role:</div><div>There are 3 distinct parts to your Helix offer: 1) Base Salary 2) Annual Bonus 3) Equity </div><ul><li class="">Expected Helix Base: <span style="background-color: transparent; color: rgb(0, 0, 0);">$97,000 - $122,500</span></li><li class="">Expected Helix Discretionary Annual Bonus: 10% of your annual salary</li><li class="">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.</li></ul><div><br></div><div>Aside from working alongside brilliant, dedicated, passionate, down-to-earth, curious, warm, and thoughtful people, we also provide great benefits:</div><ul><li class="">Comprehensive Health Insurance with Date of Hire eligibility </li><li class="">12 weeks Helix Paid Parental Leave option </li><li class="">Comprehensive Well-Being Benefits </li><li class="">Flexible PTO</li><li class="">Remote options for many roles and a home office stipend </li></ul><div><br></div><div>What To Expect During Your First 90 days:</div><ul><li class="">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.</li><li class="">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. </li><li class="">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.</li></ul><div><br></div><div>To learn how Helix collects, uses, and protects your personal information during the recruitment process, please review our <a href="https://www.helix.com/privacy-policy" rel="noopener noreferrer" target="_blank" style="color: rgb(18, 100, 163); background-color: rgb(255, 255, 255);"><u>Privacy Notice</u></a>.</div><div><br></div><div><em>Helix is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. </em></div><div><br></div><div><em> #LI-Remote</em></div>

Apply Now

Remote Opportunity

AI/ML Scientist

Join Helix as a mid professional working remotely from Canada. Explore the role, benefits, and apply in one place.

AI/ML Scientist

Helix

Full Time

$97k - $122.5k

5 weeks ago

Who We Are & What We Do 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.

Canada

Mid

Machine Learning

Python

LLM

+5 more

Job Description

Who We Are & What We Do

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. Join us in building a future where healthcare is personalized, proactive, and powered by genomics.

What is special about this role?

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, for example, germline genomes linked to longitudinal clinical records, to better understand and predict a patient's journey, taking precision medicine to a new level.

You will take ownership of impactful work early on; your results will be influential, and you will collaborate closely with domain experts. You will have direct access to data that most professionals in this field only read about, along with the opportunity to develop a deep understanding of genomic and clinical data alongside senior experts who have dedicated their careers to this work.

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. 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

About you:

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"

Pluses:

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 Interview Process:

1) Recruiter Screen 2) Manager Screen 3) Tech Screens 4) Final Loop 5) Offer

Expected Pay For This Role:

There are 3 distinct parts to your Helix offer: 1) Base Salary 2) Annual Bonus 3) Equity

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.

Aside from working alongside brilliant, dedicated, passionate, down-to-earth, curious, warm, and thoughtful people, we also provide great 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

What To Expect During Your First 90 days:

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.

To learn how Helix collects, uses, and protects your personal information during the recruitment process, please review our Privacy Notice.

Helix is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws.

#LI-Remote

Benefits

Health Insurance
Parental Leave

Skills

Machine Learning

Python

LLM

Genomics

Bioinformatics

Statistics

Data Science

Generative Models

Ready to Apply?

Join Helix today

Salary Range

$97k - $122.5k

Posted 5 weeks ago

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