AI/ML Engineer

• 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:

• 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: