Back
Remote role, popular ML engineer title, mid-level experience and broad AI skillset drive high competition.
Requires specialized ML/LLM and production ML experience, so candidate backgrounds must be domain-specific.
Explicit 6+ years plus mandatory production ML, LLM, model-serving, and cloud experience makes shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and improve production ML systems focused on classification, document understanding, retrieval, and AI-powered automation.
Fine-tune and deploy transformer-based models, including LLMs, SLMs, and related GenAI technologies, ensuring reliability, scalability, and cost-effectiveness in production.
Mentor junior engineers and lead initiatives to raise the rigor of AI/ML model evaluation, monitoring, and operational maturity.
Bachelor's degree in Computer Science, Engineering, or related technical field (B.E. explicitly mentioned).
Minimum 6 years of machine learning engineering or applied AI experience including NLP, information retrieval, or production AI systems.
Proficient in Python software engineering with experience in backend services, APIs, distributed systems, and deploying ML models in production.
Experience with transformer-based models, embeddings, RAG, document AI, real-time and batch model serving, monitoring, and cloud-native deployment.
Experienced in end-to-end production ML system delivery with strong focus on AI/ML model reliability, observability, and cost control at scale.
Comfortable navigating ambiguous technical/business problems and translating them into actionable ML solutions.
Skilled at collaborating across multi-disciplinary teams and mentoring others to improve AI engineering standards and practices.