Hands-on AI Engineer: From Prototype to Production

Socket.dev; San Francisco (CA); On-site; USD 140,000 - 230,000; Full time

Benefits offered by this job

PTO 20 days per year

Parental Leave

Rewards & Recognition

Insurance Benefits

Job summary

Innovaccer is seeking an AI Engineer to join its growing AI team and build production-grade AI systems that solve complex problems at scale. You will design, develop, and deploy AI-powered applications including LLM-based solutions and RAG-powered workflows.

The role spans end-to-end development from experimentation to production deployment, requiring strong Python, PyTorch, and systems thinking. You will collaborate with product and data teams and communicate with non-AI stakeholders.

Qualifications

• MS or PhD in Computer Science, ML, or related field; exceptional BS with research will be considered.
• First-author publications at NeurIPS/ICML/ICLR/ACL/EMNLP or meaningful open-source ML contributions.
• Fine-tuned open-weight models; explain choice of PE vs full fine-tuning.
• Strong Python and PyTorch skills; familiarity with training/serving stacks.
• Experience with multi-GPU training; understanding sharding strategies.
• Evidence you can finish projects and ship models.

Responsibilities

• Take ideas from concept to prototype to production.
• Build model layers and compose models into working systems with product-level accuracy.
• Write real code in Python and PyTorch; optimize training runs.
• Design experiments and report results that test hypotheses.
• Measure and evaluate rigorously; question seemingly good results.
• Explain AI work to non-engineers and clinicians.

Skills

Python

PyTorch

Fine-tuning

Experimentation

Communication

Multi-GPU training

Education

MS/PhD in CS/ML

Exceptional BS with research

Tools

HuggingFace

FSDP/DeepSpeed

vLLM or SGLang

Job description

Innovaccer is seeking an AI Engineer to join its growing AI team and build production-grade AI systems that solve complex problems at scale. You will design, develop, and deploy AI-powered applications including LLM-based solutions and RAG-powered workflows.

The role spans end-to-end development from experimentation to production deployment, requiring strong Python, PyTorch, and systems thinking. You will collaborate with product and data teams and communicate with non-AI stakeholders.