Research Engineer
Tessera Labs2 months ago
San Jose, CA, USA or New York, NY, USASenior
Base Salary
$200k - $300k/yr
Responsibilities
- Build and scale post-training infrastructure for SFT, preference optimization, and reinforcement learning involving long-horizon tool use and enterprise transformations.
- Develop memory, context, ontology, and knowledge-graph systems for long-running agents.
- Create data-generation and curation pipelines for synthetic landscapes, transformation traces, tool-call trajectories, and curriculum infrastructure.
- Build sandboxed RL environments and execution-and-verification harnesses with automatically scored outcomes.
- Own offline evaluation infrastructure for trajectory-level agent behavior, reproducible task suites, and long-term result tracking.
- Run experiments end to end, including design, execution, debugging, analysis, and interpretation.
- Optimize distributed training and inference throughput through kernels, parallelism, memory, batching, serving, and long-context techniques.
- Take trained models into production serving through quantization, serving configuration, and rollback planning.
- Establish standards for experiment reproducibility, tracking, and result hygiene.
Requirements
- Significant experience training, fine-tuning, or post-training language models with demonstrated results owned by the candidate.
- RL experience such as RLHF, RLAIF, RLVR, GRPO-family methods, or agentic RL is close to a requirement.
- Experience or strong understanding of memory and context for long-running agents through architecture, retrieval, or training.
- Strong software engineering fundamentals and the ability to write experiment code that others can run.
- Fluency in Python and PyTorch or JAX, with the ability to debug distributed training.
- Experience with GPU infrastructure at scale and understanding of training time and memory usage.
- Ability to design, run, and interpret rigorous experiments and distinguish effects, noise, and bugs.
- Clear written communication and interest in taking research results into production.
- Preferred experience includes RL environments, execution sandboxes, verifiable-reward task suites, long-context modeling, knowledge graphs, ontologies, semantic layers, production agent memory, code models, or open-source ML systems.
- Preferred evidence includes contributions to systems such as vLLM, SGLang, PyTorch, Triton, DeepSpeed, Ray, Megatron, or TRL; publications, technical reports, or open-source releases; and an advanced degree in a quantitative field or equivalent industry research experience.
Categories
AI ResearchML Engineering
About Tessera Labs
Tessera Labs builds multi-agent AI systems that automate complex enterprise workflows across platforms such as SAP, Salesforce, Workday, Snowflake, and Databricks. It sells AI automation software and services to large organizations seeking to operationalize AI in back-office and data operations. Founded in 2022 and headquartered in London, the privately held company focuses on deploying production AI within existing enterprise stacks.