Senior AI / ML Developer

Job Title

Senior AI/ML Developer

Job Type

Full time

Job Summary

You will independently lead applied AI solutions from feasibility and architecture through production operation. You should bring strong depth in either computer vision/deep learning or GenAI/RAG, plus hands-on experience in an adjacent AI capability. The role combines individual contribution, system design, technical leadership, and stakeholder communication.

Responsibilities

• Lead technical discovery, feasibility assessment, architecture, evaluation planning, and risk identification.
• Lead rapid proof-of-concepts to validate feasibility, customer value, and delivery risk.
• Design full-stack, production-grade AI systems across data, models, retrieval, APIs, application integration, deployment, and observability, selecting technologies against measurable requirements.
• Own a primary track: computer vision systems such as training, video analytics, and edge/cloud deployment; or GenAI systems such as RAG, hybrid retrieval, reranking, and agent/tool orchestration.
• Optimize training and inference for quality, latency, throughput, and cost through quantization, pruning, batching, caching, or hardware-aware deployment where appropriate.
• Partner with platform and DevOps teams on experiment tracking, data/model versioning, CI/CD, observability, and release controls.
• Establish regression, drift, safety, monitoring, and rollback gates; lead incident investigation and preventive improvement across models, data, and services.
• Mentor engineers, review code and architecture, and communicate trade-offs to product, business, and client stakeholders, including during technical proposals.
• Deliver polished customer demonstrations that clearly communicate technical capability and business value.
• Contribute reusable architectures, reference implementations, and technical knowledge to the internal AI Lab.

Required Qualifications

• 4+ years of relevant AI/ML or software engineering experience, including ownership of production AI systems.
• Deep expertise in computer vision/deep learning or GenAI/RAG, with practical experience in at least one adjacent AI domain.
• Strong Python engineering across API/service design, automated testing, code review, performance troubleshooting, and maintainable codebases.
• Strong fundamentals across software engineering, ML, data, evaluation, APIs, and deployment, plus full-stack AI delivery experience and a technology-agnostic approach.
• Strong customer-facing communication, presentation skills, and professional presence to run clear, reliable demonstrations.
• Experience designing evaluation frameworks using domain-appropriate measures: precision, recall, F1 or mAP; MRR or nDCG; and LLM/agent quality, groundedness, task success, safety, latency, and cost.
• Hands-on cloud or on-premises GPU infrastructure experience, including Docker, CI/CD, and multi-service debugging.
• Ability to turn ambiguous business problems into technical options, acceptance criteria, and phased plans while guiding engineers and stakeholders through trade-offs.

Preferred Qualifications

• Model optimization, serving, or fine-tuning with Triton, TensorRT, ONNX, Jetson, LoRA/QLoRA, or comparable approaches.
• Advanced RAG, agent workflows, multilingual NLP, document AI, or OCR experience.
• Enterprise AI governance or client-facing solutioning experience, including access control, privacy, auditability, model risk, or presales.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.