🛠 Tech Stack

💼 About This Role

You'll design and run experiments for a domain-specific GenAI platform, advancing model training, reinforcement learning, and multimodal understanding. You'll ship research into production, collaborating with engineering and product teams. This role stands out for its focus on regulated industries like energy and finance.

🎯 What You'll Do

• Architect and orchestrate massively parallel AI research workflows
• Design, train, and iterate on models across the full GenAI stack
• Push the frontier of domain-specific AI with rigorous research
• Build agentic research infrastructure for shared tooling
• Ship research into production at velocity

📋 Requirements

• PhD in Computer Science, Machine Learning, or related field (or MSc with 4+ years experience)
• End-to-end training of at least one neural model
• Strong knowledge of probability, optimization, and linear algebra in NLP, CV, RL, or IR
• Experience building training or evaluation pipelines with real data
• Production-quality Python with Git and collaborative development workflows

✨ Nice to Have

• Experience with distributed training frameworks (PyTorch DDP, DeepSpeed, FSDP)
• Published at top-tier venues (NeurIPS, ICML, ICLR, etc.)
• Hands-on experience with post-training methods (RLHF, DPO, reward modeling)

🎁 Benefits & Perks

• 🧑‍💻 Cutting-edge research environment
• 🏢 Fortune 500 clients and impact
• 🌍 Remote flexibility (implied)
• 📈 Career growth in fast-moving startup

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite (virtual)· 3 hours