🛠 Tech Stack

💼 About This Role

You'll lead end-to-end AI research programs at the frontier of applied research and production-grade GenAI system development for regulated enterprise environments. You'll drive improvements in domain-specific model performance through multi-stage training and reinforcement learning approaches. The role offers a highly agentic research environment with large-scale compute infrastructure.

🎯 What You'll Do

• Lead AI research programs from problem framing to production deployment.
• Improve domain-specific model performance via RL and ablation studies.
• Design multimodal AI systems and retrieval architectures.
• Build agent-orchestrated data and training pipelines.

📋 Requirements

• PhD or MSc in CS, ML, or related field.
• 5+ years AI/ML research with production impact and 2+ on LLMs.
• Hands-on with full model training pipelines (pretrain, fine-tune, post-train).
• Expertise in RLHF, multimodal learning, RAG, domain adaptation, or knowledge-grounded systems.

✨ Nice to Have

• Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron-LM).
• Strong Python engineering skills with production-quality code.
• Experience defining evaluation metrics from scratch for ambiguous problems.

🎁 Benefits & Perks

• 💰 Competitive compensation aligned with senior AI research roles.
• 🏖️ Remote-friendly work flexibility depending on location.
• 🔬 Work on cutting-edge GenAI systems deployed in regulated industries.
• 🖥️ Access to large-scale compute infrastructure and advanced AI tooling.
• 📚 Publication opportunities and external recognition.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Research Presentation· 45 min
4. 4Team Fit Interview· 30 min