Machine Learning Engineer

Role overview

Responsibilities

• Explore, implement, and benchmark ML, NLP, and generative AI methods, including LLM fine-tuning, retrieval-augmented generation, and document understanding.
• Clean, annotate, and transform case data; build reusable datasets and data loaders.
• Design experiments, run A/B tests, analyze results, and share findings with product and engineering teams.
• Integrate models into production systems with ML platform engineers, supporting testing, monitoring, and scaling.
• Collaborate with product managers, legal analysts, and software engineers to develop measurable ML solutions.
• Follow research in LLMs, representation learning, and prompt engineering, and share learnings with the team.

Qualifications

• B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a related field.
• Solid grounding in supervised and unsupervised learning, evaluation metrics, overfitting, and regularization.
• Hands-on NLP or generative AI experience, such as transformers, embeddings, sequence-to-sequence models, or LLMs.
• Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, or spaCy.
• Familiarity with SQL and basic data engineering concepts, including ETL, versioned datasets, and notebooks.
• Strong analytical thinking, clear communication, and willingness to learn and iterate quickly.

Preferred experience

• Exposure to AWS or GCP is a plus.
• Experience with Weights & Biases, Gemini Enterprise Agent Platform, or MLflow is a plus.
• Familiarity with Docker or Kubernetes is a plus.
• Experience in a high-growth startup environment is a plus.

Workplace

• Hybrid work is available from the San Francisco or Toronto office, with three days of the candidate's choice.

Benefits and perks

• Benefits for full-time employees include medical, dental, and vision plans, additional insurance options, flexible paid time off, sick leave, disability coverage, and paid parental leave.
• The package includes a home office stipend, applicable U.S. or Canadian retirement plans, and a local in-person meet-up program.
• U.S.-observed and Canadian provincial statutory holidays are provided as applicable.

Compensation

• The stated compensation range is $130K–$205K; the source does not specify a pay cadence.

Application notes

• Applications are accepted through the company's careers page; resumes or expressions of interest are not accepted by email or social media.
• Interview recording is optional and requires candidate consent.