Senior ML Encoder

Dawar Consulting, Inc.; South San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical

Paid Sick Leave

401 (k)

Job summary

Dawar Consulting, Inc. in South San Francisco, CA is seeking a Senior ML Encoder Lead to develop shared customer representations from longitudinal data, define objectives, and build embedding models.

You will produce production-ready code, evaluate models with time-based splits, and present findings to senior stakeholders. The role emphasizes scalable ML pipelines, deployment readiness, and collaboration with cross-functional teams.

Qualifications

• Proven experience training encoder/embedding models and pretraining objectives.
• Expertise in representation learning (self-supervised/transformers).
• Experience with large-scale, sparse longitudinal data.
• Ability to develop inductive representations with limited history.
• Strong evaluation: time-based splits, leakage detection, robust baselines.
• Strong Python skills with PyTorch or JAX, SQL, cloud training.
• Experience bringing ML from research to production with pipelines and monitoring.

Responsibilities

• Define modeling objectives and build encoder/embedding models.
• Develop production-ready code and data pipelines.
• Evaluate approach for downstream value and communicate results.

Skills

Encoder training

Representation learning

Time-based splits

Python

PyTorch

JAX

SQL

Distributed processing

Cloud training

Production pipelines

Communication

Tools

PyTorch

JAX

AWS

GCP

Job description

Job Description

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

Location: South San Francisco, CA

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

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

Seeking a seniorML 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 experience personally training encoder or embedding models and designing pretraining objectives.
• Deep expertise in representation 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 developing inductive representations for 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 for incremental signal, calibration, stability, drift, and subgroup performance.
• Strong Python skills with PyTorch 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

• Customer-360 representations, behavioral embeddings, recommender systems, or foundation models.
• 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.