Senior Lead ML Encoder

Dawar Consulting, Inc.; South San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Medical benefits

Paid sick leave

401(k)

Job summary

Dawar Consulting, Inc. in South San Francisco seeks a Senior ML Encoder Lead to develop shared representations from longitudinal data, define modeling objectives, and deliver production-ready code.

The role emphasizes encoder training, evaluation, and collaboration with senior stakeholders. Ideal candidates will have deep experience in representation learning, large-scale data, and Python/PyTorch or JAX, with a track record of moving models from research to production and communicating findings

Qualifications

• Proven experience personally training encoder or embedding models.
• Deep expertise in representation learning including self-supervised/contrastive methods.
• Experience with large-scale, sparse, longitudinal data such as transactions or journeys.
• Experience developing inductive representations for entities with limited history.
• Strong model evaluation skills with time-based splits, leakage detection, and robust baselines.
• Ability to evaluate embeddings for incremental signal, calibration, and drift.
• Strong Python skills with PyTorch or JAX, SQL, distributed processing, and cloud training.
• Experience taking ML models from research to production with pipelines and monitoring.
• Strong communication to present findings and recommendations to senior stakeholders.

Responsibilities

• Develop encoder/embedding models and define modeling objectives.
• Build production-ready code and data pipelines for representations.
• Evaluate embeddings for downstream value and stability across segments.
• Collaborate with stakeholders to interpret results and guide decisions.

Skills

Encoder training

Representation learning

Longitudinal data

Inductive representations

Model evaluation

Embedding analysis

Python

PyTorch

JAX

SQL

Production ML

Communication

Job description

Senior ML Encoder

South San Francisco, United States | Posted on 08/26/2026

Our client, a world leader in biotechnology and life sciences, is looking for a \"Senior ML Encoder\".

Job Duration: Long-Term Contract (Possibility Of Extension)

Company Benefits: Medical, Paid Sick Leave, 401 (k)

Seeking a senior ML Encoder Lead to develop shared customer representations from longitudinal transaction, sales, and interaction data. The ideal candidate will independently define modeling objectives, build and evaluate encoder/embedding models, develop production-ready code, and determine whether the approach provides meaningful downstream value.

Required Skills & Qualifications

• Proven experiencepersonally training encoder or embedding modelsand designing pretraining objectives.
  
• Deep expertise inrepresentation learning, including self-supervised/contrastive learning, sequence/temporal modeling, transformers, GNNs, or recommender embeddings.
  
• Experience with large-scale, sparse, longitudinal event data such as transactions, clickstreams, customer journeys, or engagement histories.
  
• Experience developinginductive representationsfor entities with limited historical data.
  
• Strong model evaluation skills, including time-based splits, leakage detection, cold-start analysis, uncertainty, and robust baselines.
  
• Ability to evaluate embeddings forincremental signal, calibration, stability, drift, and subgroup performance.
  
• StrongPythonskills withPyTorch or JAX, SQL, distributed data processing, and cloud-based model training.
  
• Experience taking ML models from research to production, including pipelines, data contracts, versioning, serving, monitoring, and reproducibility.
  
• Strong communication skills with the ability to present findings, uncertainty, and recommendations to senior stakeholders.
  

Preferred Skills

• Knowledge of privacy, fairness, and re-identification risks in learned representations.
  
• Publications, patents, or public applied work in representation learning.
  
• Experience with large-scale behavioral data in consumer technology, marketplaces, streaming, financial services, payments, or advertising technology.