TriFetch is a company focused on AI and machine learning solutions, and they are seeking a Founding AI/Machine Learning Engineer. The role involves architecting post-training stacks, leveraging ...
Trifetch
1 job near Columbus, OH
TriFetch is a company focused on AI and machine learning solutions, and they are seeking a Founding AI/Machine Learning Engineer. The role involves architecting post-training stacks, leveraging ...
Full-time
Re-posted 15 days ago
Job description
Job Summary:
TriFetch is a company focused on AI and machine learning solutions, and they are seeking a Founding AI/Machine Learning Engineer. The role involves architecting post-training stacks, leveraging proprietary data for model fine-tuning, and collaborating with co-founders to define the research roadmap.
Responsibilities:
• Architect the Post-Training Stack: Lead the design and execution of alignment pipelines (SFT, RLHF, RLAIF) that bridge the gap between "exam-passing" models and "clinically useful" systems.
• Leverage Proprietary Data: Utilize our proprietary and open source medical datasets to fine-tune models on edge cases that generic models miss.
• Novel Technique Experimentation: Research and implement cutting-edge post-training methods to optimize model performance, aiming for improvements in calibration and reliability critical for healthcare.
• Safety & Evaluation: Build rigorous evaluation frameworks (LLM-as-a-judge, benchmarks) to detect hallucinations, ensure clinical correctness, and guarantee safety before deployment.
• Strategic Collaboration: Work directly with the co-founders to define the research roadmap and platform strategy.
Qualifications:
Required:
• Hands-on experience with post-training models for specific applications (SFT, RLHF, RLAIF, Reward Modeling, Knowledge Distillation, etc)
• Deep understanding of Transformer architectures (attention mechanisms, positional encodings) and ML systems
• Experience with distributed training frameworks and optimizing training jobs on GPU clusters
• You thrive in ambiguous environments, learn quickly, and have a bias toward action
• Proficiency in Python, PyTorch
• Familiarity with the modern open-source LLM stacks (HuggingFace, Vertex, Vercel, etc.)
Preferred:
• Healthcare experience
• Published research in high-impact journals or top-tier ML/AI conferences (NeurIPS, ICML, ICLR, CVPR, ACL)
• Background working or interning at top research labs (e.g., FAIR, DeepMind, OpenAI, Google DM, MSR, Stanford/CMU/MIT labs)
• Experience dealing with multimodal health data, clinical reasoning, or safety-critical ML systems
• You have founded a company, built early-stage products, or enjoy the 'zero-to-one' phase of building
Company:
TriFetch is a San Francisco-based healthcare AI startup focused on bridging AI foundations with practical healthcare applications. Founded in 2024, the company is headquartered in San Francisco, USA, with a team of 2-10 employees. The company is currently Early Stage.
TriFetch is a company focused on AI and machine learning solutions, and they are seeking a Founding AI/Machine Learning Engineer. The role involves architecting post-training stacks, leveraging proprietary data for model fine-tuning, and collaborating with co-founders to define the research roadmap.
Responsibilities:
• Architect the Post-Training Stack: Lead the design and execution of alignment pipelines (SFT, RLHF, RLAIF) that bridge the gap between "exam-passing" models and "clinically useful" systems.
• Leverage Proprietary Data: Utilize our proprietary and open source medical datasets to fine-tune models on edge cases that generic models miss.
• Novel Technique Experimentation: Research and implement cutting-edge post-training methods to optimize model performance, aiming for improvements in calibration and reliability critical for healthcare.
• Safety & Evaluation: Build rigorous evaluation frameworks (LLM-as-a-judge, benchmarks) to detect hallucinations, ensure clinical correctness, and guarantee safety before deployment.
• Strategic Collaboration: Work directly with the co-founders to define the research roadmap and platform strategy.
Qualifications:
Required:
• Hands-on experience with post-training models for specific applications (SFT, RLHF, RLAIF, Reward Modeling, Knowledge Distillation, etc)
• Deep understanding of Transformer architectures (attention mechanisms, positional encodings) and ML systems
• Experience with distributed training frameworks and optimizing training jobs on GPU clusters
• You thrive in ambiguous environments, learn quickly, and have a bias toward action
• Proficiency in Python, PyTorch
• Familiarity with the modern open-source LLM stacks (HuggingFace, Vertex, Vercel, etc.)
Preferred:
• Healthcare experience
• Published research in high-impact journals or top-tier ML/AI conferences (NeurIPS, ICML, ICLR, CVPR, ACL)
• Background working or interning at top research labs (e.g., FAIR, DeepMind, OpenAI, Google DM, MSR, Stanford/CMU/MIT labs)
• Experience dealing with multimodal health data, clinical reasoning, or safety-critical ML systems
• You have founded a company, built early-stage products, or enjoy the 'zero-to-one' phase of building
Company:
TriFetch is a San Francisco-based healthcare AI startup focused on bridging AI foundations with practical healthcare applications. Founded in 2024, the company is headquartered in San Francisco, USA, with a team of 2-10 employees. The company is currently Early Stage.