Markovate - AI/ML Engineer - NLP/LangChain

Job Overview :

We are seeking an experienced AI/ML Engineer to lead ground-breaking projects in Generative AI, Computer Vision, NLP, Large Language Models (LLMs), and Deep Learning.

This is your chance to work with a dynamic, forward-thinking team, drive innovation, and develop scalable AI-powered full-stack applications that solve real-world problems.

What Makes This Role Exciting :

- Lead mission-critical AI initiatives from concept to production.

- Architect and deliver scalable GenAI and ML systems with measurable impact.

- Work directly with transformer models, LLMs, and cutting-edge computer vision techniques.

- Shape AI strategy while mentoring high-performing engineers.

- Own the entire ML lifecycle from data ingestion to model monitoring.

- Build for scale using Docker, FastAPI, AWS/GCP, and MLOps frameworks.

- Collaborate with product, data, and engineering teams.

- Be part of a high-growth, innovation-first culture where your work has real influence.

What Youll Do :

- Design and deploy ML and GenAI models for forecasting, recommendation engines, NLP, and computer vision.

- Provide architectural direction, perform code reviews, and mentor a growing AI team.

- Own and manage complete ML pipelines: data engineering, model training, deployment, and monitoring.

- Apply MLOps best practices: versioning, retraining, CI/CD, and performance tracking.

- Integrate AI into full-stack applications and APIs.

- Stay current with the latest developments in LLMs, vision transformers, foundation models, and emerging trends in AI/ML.

What We're Looking For :

- 3+ years of experience in AI/ML or data science.

- Proficient in Python, TensorFlow/PyTorch, and GenAI frameworks (e.g., Hugging Face Transformers, LangChain, OpenAI API).

- Strong experience with computer vision (OpenCV, YOLO, segmentation models) or agent-based AI systems.

- Proven experience deploying models in production using Docker, FastAPI, and cloud platforms (AWS/GCP/Azure).

- Hands-on with MLOps tools like MLflow, Airflow, and CI/CD pipelines.

- Deep understanding of model performance tuning, evaluation, and lifecycle management.

- Bonus: Exposure to full-stack development (JavaScript, Node.js, React).

- Strong communication, problem-solving skills, and a collaborative leadership style.