Senior Machine Learning Engineer

*Design, develop, and deploy AI and ML solutions using LangChain, TensorFlow, PyTorch, and Hugging Face.

• Build and maintain data pipelines (ETL/ELT) for structured and unstructured data using tools such as Airflow, Azure Data Factory, or AWS Glue.
• Implement and optimize LLM applications, including Retrieval-Augmented Generation (RAG) using vector databases (Pinecone, FAISS, Weaviate).
• Deploy and monitor models on Azure Machine Learning, AWS SageMaker, Bedrock, and open-source MLOps frameworks such as MLflow or Kubeflow.
• Develop APIs (REST, GraphQL) for seamless integration of AI models into business applications.
• Apply security and compliance best practices, including RBAC, encryption, and responsible AI guardrails.
• Optimize infrastructure for cost efficiency, scalability, and performance using Docker, Kubernetes, and serverless architectures.
• Automate workflows with Terraform, Bicep, or AWS CDK for cloud infrastructure provisioning.
• Collaborate with stakeholders to translate business needs into AI solutions with measurable impact.

We are seeking a Senior Machine Learning Engineer to design, build, and deploy end-to-end AI solutions across Azure, AWS, and open-source platforms. This role requires deep expertise in LLMs, deep learning, and MLOps, with the ability to manage the entire life cycle from data ingestion and transformation to production deployment and ongoing monitoring. The ideal candidate thrives in a hands-on environment, working independently to deliver secure, compliant, and scalable AI systems that generate measurable business value., * 5+ years of experience in machine learning, AI application development, or related engineering roles.

• Proven track record of delivering production-grade AI systems in multi-cloud environments.
• Strong programming skills in Python and SQL, with solid software engineering practices (testing, CI/CD, version control).
• Experience with LLMs and Generative AI development, fine-tuning, and deployment.
• Hands-on expertise in multi-cloud ML services (Azure ML, AWS SageMaker, Bedrock) and open-source frameworks.
• Proficiency in designing scalable APIs and integrating AI into enterprise architectures.
• Strong problem-solving skills with the ability to work independently and deliver on deadlines.