The Role
Develop shared customer representations from longitudinal transaction, sales, and interaction data. Define modeling objectives, train and evaluate encoder and embedding models, assess downstream value, and deliver production-ready machine learning systems. Responsibilities include representation learning, temporal modeling, inductive representations, robust evaluation, leakage and cold-start analysis, calibration, drift monitoring, subgroup performance, and research-to-production deployment. Present findings and recommendations to senior stakeholders while addressing privacy, fairness, and re-identification risks.
Summary Generated by Built In
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 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 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.
- 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.
Skills Required
- Proven experience personally training encoder or embedding models and designing pretraining objectives.
- Deep expertise in representation learning, including self-supervised or contrastive learning, sequence or 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 machine learning 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.
- Experience with 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.
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Dawar Consulting Inc. is a professional services and staff augmentation firm specializing in IT consulting, workforce solutions, and HCM/HRIS services. They provide technology and business consulting, project delivery, and IT support to help clients achieve their strategic goals. With expertise across IT, Engineering, and Finance, they deliver best-in-class workforce solutions and innovative strategies to drive operational efficiency and business success.
