Senior Machine Learning Engineer (LLMs, MLOps, Computer Vision & Cloud AI)

Skills:

Machine Learning, Generative AI, LLMs, GPT, BERT, T5, Hugging Face, Ollama, Prompt Engineering, RAG, NLP, Python, PyTorch, TensorFlow, Computer Vision, OpenCV, YOLO, Object Detection, Image Segmentation, MLOps, MLflow, Kubeflow, Airflow, Weights,AWS, Azure, GCP, OCI, SageMaker, Bedrock, Vertex AI, Azure AI, Docker, Kubernetes, Ansible, CI/CD, Azure DevOps, GitHub Actions

We are seeking a highly skilled Senior Machine Learning Engineer to design, develop, deploy, and optimize AI/ML solutions in production environments. The ideal candidate will have strong experience with cloud platforms, large language models (LLMs), MLOps, computer vision, recommender systems, time-series forecasting, and scalable machine learning infrastructure. This role will work closely with data scientists, software engineers, DevOps teams, and business stakeholders to deliver innovative AI-powered solutions.

Key Responsibilities

• Design, develop, deploy, and maintain production-grade machine learning and AI solutions.
• Build and optimize Large Language Model (LLM) applications using GPT, BERT, T5, Hugging Face, Ollama, and similar technologies.
• Develop Retrieval-Augmented Generation (RAG) systems, prompt engineering strategies, and fine-tuning workflows.
• Implement and maintain MLOps pipelines using MLflow, Kubeflow, Airflow, Weights & Biases, or similar tools.
• Deploy and manage AI workloads across AWS, Azure, GCP, and OCI cloud environments.
• Design and support scalable infrastructure using Docker, Kubernetes, Ansible, and CI/CD pipelines.
• Develop machine learning models for forecasting, anomaly detection, predictive analytics, and real-time monitoring.
• Build recommendation engines, personalization platforms, ranking systems, and collaborative filtering solutions.
• Develop and deploy computer vision solutions using PyTorch, TensorFlow, OpenCV, YOLO, object detection, and image segmentation techniques.
• Implement feature engineering strategies and feature stores such as Feast or Tecton.
• Optimize model performance using quantization, pruning, knowledge distillation, and inference acceleration techniques.
• Support distributed model training across multi-GPU and multi-node environments.
• Design and manage SQL, NoSQL, and vector database solutions for AI applications.
• Automate infrastructure provisioning, deployments, monitoring, and operational support activities.
• Collaborate with cross-functional teams to identify AI opportunities and deliver business-focused solutions.
• Maintain AI governance, security, compliance, and operational best practices.

Required Qualifications

• 8+ years of experience in cloud platforms including AWS, Azure, GCP, or OCI.
• 8+ years of experience with DevOps technologies including Docker, Kubernetes, Ansible, and CI/CD automation.
• Strong experience with SQL databases (PostgreSQL, MySQL) and NoSQL/vector databases.
• Proficiency in Bash and PowerShell scripting for automation and infrastructure management.
• Experience with Azure DevOps, GitHub Actions, Jenkins, or similar CI/CD platforms.
• 3+ years of hands-on Python development experience in production environments.
• 3+ years of experience with NLP, LLMs, transformers, prompt engineering, RAG, and AI application development.
• Experience building and deploying machine learning models serving real-world users.
• Experience with time-series forecasting, anomaly detection, and predictive analytics.
• Experience developing recommendation systems and personalization engines.
• Experience with distributed training, model optimization, and scalable AI infrastructure.
• Strong problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Experience with GIS, geospatial analytics, and spatial data processing.
• Background in transportation, logistics, smart city, or infrastructure-focused solutions.
• Experience applying computer vision to infrastructure monitoring, vehicle analytics, or public sector use cases.
• Familiarity with public sector compliance, security, and governance standards.
• Experience with Unreal Engine, digital twin technologies, and simulation platforms.
• Experience with Google Maps, Cesium API, and geospatial visualization tools.
• Experience with Polygonflow Dash and related digital twin technologies.