AI/ML Engineer

F2F Walkin Drive - 14th Feb 2026 Location: Hyderabad  Accountabilities:

• Design, develop, train, and deploy production-grade ML and GenAI models across use cases including NLP, computer vision, and structured data modeling.
• Leverage frameworks such as TensorFlow, Keras, PyTorch, and LangChain to build scalable deep learning and LLM-based solutions.
• Develop and maintain end-to-end ML pipelines with reusable, modular components for data ingestion, feature engineering, model training, and deployment.
• Implement and manage models on cloud platforms such as AWS, GCP, or Azure using services like SageMaker, Vertex AI, or Azure ML.
• Apply MLOps best practices using tools like MLflow, Kubeflow, Weights & Biases, Airflow, DVC, and Prefect to ensure scalable and reliable ML delivery.
• Incorporate CI/CD pipelines (using Jenkins, GitHub Actions, or similar) to automate testing, packaging, and deployment of ML workloads.
• Containerize applications using Docker and orchestrate scalable deployments via Kubernetes.
• Integrate LLMs with APIs and external systems using LangChain, Vector Databases (e.g., FAISS, Pinecone), and prompt engineering best practices.
• Collaborate closely with data engineers to access, prepare, and transform large-scale structured and unstructured datasets for ML pipelines.
• Build monitoring and retraining workflows to ensure models remain performant and robust in production.
• Evaluate and integrate third-party GenAI APIs or foundational models where appropriate to accelerate delivery.
• Maintain rigorous experiment tracking, hyper parameter tuning, and model versioning.
• Champion industry standards and evolving practices in ML lifecycle management, cloud-native AI architectures, and responsible AI.
• Work across global, multi-functional teams, including architects, principal engineers, and domain experts.

Essential Skills / Experience:

• 2–10 years of hands-on experience in developing, training, and deploying ML/DL/GenAI models.
• Strong programming expertise in Python with proficiency in machine learning, data manipulation, and scripting.
• Demonstrated experience working with Generative AI models and Large Language Models (LLMs) such as GPT, LLaMA, Claude, or similar.
• Hands-on experience with deep learning frameworks like TensorFlow, Keras, or PyTorch.
• Experience in LangChain or similar frameworks for LLM-based app orchestration.
• Proven ability to implement and scale CI/CD pipelines for ML workflows using tools like Jenkins, GitHub, GitLab, or Bitbucket Pipelines.
• Familiarity with containerization (Docker) and orchestration tools like Kubernetes.
• Experience working with cloud platforms (AWS, Azure, GCP) and relevant AI/ML services such as SageMaker, Vertex AI, or Azure ML Studio.
• Knowledge of MLOps tools such as MLflow, Kubeflow, DVC, Weights & Biases, Airflow, and Prefect.
• Strong understanding of data engineering concepts, including batch/streaming pipelines, data lakes, and real-time processing (e.g., Kafka).
• Solid grasp of statistical modeling, machine learning algorithms, and evaluation metrics.
• Experience with version control systems (Git) and collaborative development workflows.
• Ability to translate complex business needs into scalable ML architectures and systems.

Why Join Us?

• Build and deploy cutting-edge LLM and GenAI applications that solve real-world problems
• Collaborate with thought leaders across engineering, product, and data science
• Work in a dynamic, cloud-native, and automation-driven AI environment
• Accelerate your growth through certification programs and continuous learning
• Be part of an innovation-first team that values openness, agility, and integrity

About Agilisium:
 

• Agilisium, is an AWS technology Advanced Consulting Partner that enables companies to accelerate their "Data-to-Insights-Leap.
• With $50+ million in annual revenue and over 30% year-over-year growth, Agilisium is one of the fastest-growing IT solution providers in Southern California.
• Our most important asset? People.
• Talent management plays a vital role in our business strategy.