or apply directly on Lila Sciences's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 54 days Lila Sciences's roles stay open a median of 55 days
- Reposted
- No
- Salary listed
- No 0% of Lila Sciences's roles list one
- Ghost-job risk at Lila Sciences
- high 104 stale, 2 reposted of 118 open
- Hiring momentum
- 155 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-27
Measured from postings appearing on and disappearing from Lila Sciences's own greenhouse board since 2026-08-03. Full hiring picture for Lila Sciences.
About this role
As a Senior or Principal ML Engineer at Lila, you will lead research on structure prediction and co-folding models, focusing on protein interactions to support antibody design. Your role involves owning the entire ML process from problem formulation to model training and evaluation, collaborating closely with experimental scientists, and representing Lila's research in the scientific community. You will also contribute to advancing research standards and methodologies within the foundation models program.
- benefits
- 4/5
- freshness
- 1/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Lila Sciences as an employer.
What you need
- PhD in Computer Science, Machine Learning, Computational Biology, Biophysics, or a related quantitative field
- Demonstrated ability to formulate and drive research programs independently, from problem definition through publication and deployment
- Fluency across ML and at least one life science domain (structural biology, protein engineering, molecular biology, genomics, or related)
- Strong track record of cross-functional collaboration with experimental scientists
- Expertise in ML frameworks (PyTorch, JAX, or TensorFlow)
- Experience with large-scale distributed training infrastructure (AWS, GCP, or on-prem clusters)
Nice to have
- Strong expertise in structure prediction, co-folding, geometric deep learning, or structure-aware molecular ML
- Experience with AlphaFold or AlphaFold-derived methods
- Experience in computational protein design, particularly antibody and nanobody engineering
- Strong expertise in generative model architectures and training
- Experience designing biological sequences or molecular structures with demonstrated wet-lab validation
What you get
- Competitive base compensation with bonus potential and generous early-stage equity
- Comprehensive benefits program including medical, dental, and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with generous company-wide holidays
- Paid parental leave
- Educational assistance program
Worth weighing
- No salary listed beyond the range of $252,000 to $374,000 USD
- The role involves high-impact independent contributions, which may require significant self-direction and initiative
- The focus on collaboration with experimental scientists may require strong interpersonal skills and adaptability to different working styles
Summarised from Lila Sciences's posting. Read the full original.
Listed by Lila Sciences on their greenhouse job board, last confirmed open on 2026-09-27. PitchMeAI is not the employer.
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