AI / ML Engineer – MLOps Specialist (5-10 Years Exp)

HypTechie; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

HypTechie in Bengaluru, India is seeking a skilled AI/ML Engineer with deep MLOps expertise to lead the design, implementation, and maintenance of scalable ML systems. You will operationalize AI/ML models, build robust pipelines, deploy in production with Docker and FastAPI, and monitor performance at scale.

You will collaborate across teams on GenAI initiatives and multi-cloud infrastructure while mentoring junior engineers.

Qualifications

• 5+ years of hands-on MLOps experience.
• Strong Python programming skills.
• Proven experience with Docker, FastAPI.
• Experience with MLflow and Apache Airflow is mandatory.
• Experience with cloud-based AI services (AWS, Azure, GCP).
• Proficient in CI/CD pipelines and automation tools.
• Knowledge of model performance monitoring, retraining, and optimization techniques.
• Familiarity with TensorFlow, PyTorch, Scikit-learn.
• Exposure to multi-cloud environments is a strong plus.
• Excellent problem-solving and collaboration skills.

Responsibilities

• Lead design, development, and operationalization of machine learning models.
• Build and manage ML pipelines for training, validation, deployment, and monitoring.
• Deploy models in containerized environments using Docker, and expose them via FastAPI.
• Implement CI/CD pipelines using tools like GitHub Actions to support rapid and reliable deployments.
• Manage batch and real-time inference pipelines, ensuring scalable and low-latency performance.
• Oversee model lifecycle management, including version control, packaging, model registry (e.g., MLflow), and governance.
• Set up monitoring, alerts, and dashboards to track model performance, data drift, and system health.
• Lead optimization and retraining strategies to maintain long-term model accuracy.
• Mentor junior engineers and collaborate with cross-functional teams to drive key architectural and operational decisions.

Skills

MLOps

Python

Docker

FastAPI

CI/CD

MLflow

Airflow

Cloud services

Kubernetes

GenAI

Monitoring

Tools

MLflow

Apache Airflow

Job description

Location: Bengaluru, India

Experience Required: 5 to 10 Years

Educational Qualification: 15 Years Full-Time Education

Employment Type: Full-Time

Job ID: ATCI-5104770-S1887672

Primary Skill: Machine Learning Operations (MLOps)

About the Role

We are looking for a skilled AI / ML Engineer with deep expertise in MLOps to lead the design, implementation, and maintenance of scalable machine learning systems. You will be responsible for the operationalization of AI/ML models, including building and managing robust pipelines, deploying models to production, and monitoring performance at scale. In this role, you will work on the cutting edge of AI/ML, including Generative AI (GenAI), cloud-based AI services, and modern infrastructure frameworks. You’ll collaborate across teams to ensure end-to-end delivery of production-grade ML solutions.

Key Responsibilities

• Lead the design, development, and operationalization of machine learning models.
• Build and manage ML pipelines for model training, validation, deployment, and monitoring.
• Deploy models in containerized environments using Docker, and expose them via FastAPI or similar frameworks.
• Implement CI/CD pipelines using tools like GitHub Actions to support rapid and reliable deployments.
• Manage batch and real-time inference pipelines, ensuring scalable and low-latency performance.
• Oversee model lifecycle management, including version control, packaging, model registry (e.g., MLflow), and governance.
• Set up monitoring, alerts, and dashboards to track model performance, data drift, and system health.
• Lead optimization and retraining strategies to maintain long-term model accuracy.
• Mentor junior engineers and collaborate with cross-functional teams to drive key architectural and operational decisions.

Required Skills & Qualifications

• Minimum 5 years of hands-on experience in Machine Learning Operations (MLOps).
• Strong Python programming skills, with proven experience in model development and deployment.
• Solid experience with Docker, FastAPI, and orchestration tools.
• Experience with MLflow and Apache Airflow is mandatory.
• Experience with cloud-based AI services (AWS, Azure, GCP) and infrastructure requirements for ML systems.
• Proficient in CI/CD pipelines and automation tools.
• Good understanding of model performance monitoring, retraining, and optimization techniques.
• Familiarity with multiple ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.
• Exposure to multi-cloud environments is a strong plus.
• Excellent problem-solving, communication, and collaboration skills.

Good to Have

• Experience with Generative AI (GenAI) model deployment.
• Familiarity with Kubernetes and cloud-native MLOps tools.
• Knowledge of responsible AI practices, data governance, and explainability.

Why Join Us

• Work on cutting-edge AI initiatives, including GenAI and scalable ML systems.
• Join a highly collaborative, innovation-focused team.
• Lead the development of enterprise-grade AI/ML platforms.
• Enjoy a culture of continuous learning, mentorship, and growth.
• Competitive compensation and benefits package.