Machine Learning Engineer III

Location: South End Circle

Machine Learning Engineer III – LLM Training (RL + PEFT)

On-site, Bangalore

Latent Force

About the Role

We are building specialized LLMs that understand and reason over massive enterprise codebases. This is real model training — RL loops, PEFT, verifiable rewards, long-context modeling — not API integration. You’ll own end-to-end experimentation and work directly with founders.

Responsibilities

- Train LLMs using RL (PPO/GRPO/RLHF/RLVR) and PEFT (LoRA, QLoRA, DoRA, IA3).
- Build custom training loops with PyTorch, Hugging Face, TRL, Unsloth.
- Design reward functions and verifiers for code-understanding tasks.
- Run full-stack ML experiments: data → training → eval → iteration.
- Develop scalable training infra (FSDP/Deep Speed, distributed training).
- Build evaluation suites for reasoning and code comprehension.

- Minimum Qualifications

- 3+ years of real deep learning experience (actual model training).
- Strong fundamentals: linear algebra, probability, optimization, statistics.
- Proven experience training transformers or large DNNs from scratch or checkpoints.
- Proficiency in PyTorch, Hugging Face, TRL, Unsloth.
- Experience implementing RL algorithms or custom training pipelines.
- Research exposure (publications/preprints) or strong open-source work.
- Ability to debug training issues (NaNs, KL drift, reward hacking, etc.).
- Startup mindset; comfortable with fast, on-site, high-performance execution.

- Nice to Have

- Deep Speed/FSDP, model parallelism, vLLM.
- Program analysis / AST tooling.
- Long-context modeling experience.

- Why Join Us

- Build specialized LLMs at a well-funded early-stage company.
- Direct work with founders; high ownership and technical depth.
- High-impact role shaping core training architecture.

Apply here: (Use the "Apply for this Job" box below). Xy Bjb U8g FC
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