ML Encoder Lead

Location: San Francisco CA

Onsite Flexibility: Hybrid

• Position Type: Contract
• Contract Duration: 4 months
• Pay Rate: $80.00$100.00 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Our client is seeking a senior hands-on ML Encoder Lead to design and train a shared customer representation model using large-scale longitudinal transaction sales and interaction data. This role will define the modeling objective develop and evaluate encoder/embedding approaches and determine whether the model provides meaningful downstream value for GenAI and analytics use cases.

The teams preference is for candidates to be based on the West Coast ideally in San Francisco. Remote candidates will also be considered provided they can work Pacific Time hours.

• Design and train encoder or embedding models using longitudinal customer/event data.
• Define pretraining objectives modeling approach evaluation design and success criteria.
• Build inductive representations that can support customers/entities with limited history.
• Evaluate model performance using time-based splits cold-start slices leakage detection drift calibration and transfer to downstream tasks.
• Build production-ready training pipelines data contracts model versioning serving monitoring and reproducibility practices.
• Present findings uncertainty limitations and go/no-go recommendations to senior stakeholders.

• Hands-on experience personally training encoder or embedding models.
• Deep expertise in representation learning self-supervised or contrastive learning sequence/temporal modeling transformers GNNs or recommender embeddings.
• Experience with large sparse longitudinal event data such as transactions claims clickstream customer journeys or engagement histories.
• Strong Python PyTorch or JAX SQL distributed data processing and cloud model training experience.
• Strong evaluation discipline and ability to identify whether embeddings create true incremental signal.

• Customer-360 behavioral embeddings recommender systems or foundation models over event data.
• Privacy fairness and re-identification risk experience.
• Publications patents or public applied work in representation learning.

• Senior-level experience (510 years) in machine learning engineering or applied ML research with demonstrated hands-on ownership of encoder or embedding model development.

• Medical Vision and Dental Insurance Plans
• 401k Retirement Fund

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking financial services technology life sciences biotech utilities and retail sectors throughout the U.S. and Canada.

Job Number: 26-11383

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