Machine Learning Engineer

Machine Learning Engineer

Location: Bangalore | Hyderabad | Pune | Chennai | Mumbai | Gurgaon | Remote

About Company

Join a fast-growing AI-first technology company building intelligent industrial software that combines machine learning, large language models, and domain expertise to transform asset reliability and industrial operations. The engineering team develops scalable AI platforms that power autonomous diagnostics, predictive maintenance, root-cause analysis, and decision-making for complex industrial environments.

Job Roles & Responsibilities

• Design, deploy, and operate production-grade machine learning and LLM systems across cloud and edge environments.
• Build and maintain automated CI/CD pipelines for model training, validation, deployment, versioning, and production serving.
• Monitor model performance through observability, drift detection, evaluation pipelines, and production-quality monitoring.
• Develop and optimize LLMOps workflows covering prompt management, inference optimization, evaluation, guardrails, and model lifecycle management.
• Improve platform reliability, scalability, reproducibility, and security using modern MLOps best practices and cloud-native infrastructure.
• Collaborate with AI researchers, software engineers, platform teams, and product stakeholders to deliver production-ready ML and Generative AI capabilities.

Ideal Candidate Profile

• Bachelor's degree in Engineering, Computer Science, or a related technical discipline with 3+ years of experience in MLOps, ML platform engineering, or machine learning infrastructure.
• Strong experience deploying, serving, monitoring, and maintaining machine learning models in production environments.
• Hands-on expertise with MLflow, Docker, Kubernetes (or K3s), CI/CD pipelines, and cloud platforms including AWS, Azure, GCP, and Databricks.
• Experience operating LLM-based applications, including inference serving, evaluation pipelines, guardrails, prompt management, and production monitoring.
• Strong Python programming skills with excellent software engineering, debugging, automation, and problem-solving capabilities.
• Experience with open-source LLMs, inference frameworks such as vLLM, Triton, TGI, or Ollama, edge deployments, or industrial IoT environments is a strong advantage.

What We Offer

• Opportunity to build production-scale AI infrastructure powering next-generation industrial intelligence and autonomous decision-making systems.
• High ownership across MLOps, LLMOps, cloud infrastructure, AI platform engineering, and production machine learning systems.
• Work closely with experienced AI researchers, platform engineers, and product teams while solving challenging real-world machine learning problems.
• Remote-first work environment with exposure to cutting-edge Generative AI, cloud-native infrastructure, and large-scale ML platform engineering.

Hiring Process

Round 1: Flexiple Interview focused on machine learning infrastructure, MLOps, Kubernetes, cloud platforms, Python, communication, notice period, and compensation expectations.

Round 2: Flexiple Profile Review to validate production ML experience, platform engineering expertise, and overall role fit before client submission.

Round 3: Introductory Discussion covering technical background, startup fit, and AI platform experience.

Round 4: Technical Interview 1 assessing MLOps, cloud infrastructure, CI/CD, model deployment, and ML platform engineering.

Round 5: Technical Interview 2 evaluating LLMOps, system design, production AI architecture, and engineering depth.

Round 6: Culture Fit Discussion focused on ownership, collaboration, startup mindset, and long-term growth.

Round 7: Offer Discussion.

Hiring Process

Flexiple Interview → Profile Review → Intro Round → Tech Round 1 → Tech Round 2 → Culture Fit Round → Offer Discussion

Applications are being reviewed this week. Apply today to be included in the first round of interviews.

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