AI/Machine Learning Engineer
- India
- Permanent
- Full-time
- Create end-to-end workflows for the training and inference pipeline of the machine learning models.
- Responsible for designing, developing, and implementing multi-step RAG (Retrieval-Augmented Generation), agentic, or tool-augmented workflows using Python and frameworks like LangChain and LangGraph.
- Know the latest advancements in agentic AI, large language model (LLM) orchestration, and tools within the Python ecosystem.
- Build and optimize RAG pipelines using vector stores such as FAISS, AWS OpenSearch.
- Implement solutions for processing and analyzing time series data using libraries like Pandas and NumPy, enhancing data-driven decision-making.
- Write, evaluate, and optimize prompts for LLMs to improve the accuracy and efficiency of AI-driven applications.
- Collaborate with other developers to create, deploy, and maintain applications for different platforms.
- Write and review code for multiple applications, ensuring high quality and readability.
- Conduct unit testing and integration analysis to refine product performance.
- Ensure consistency between delivered product features and business requirements.
- Optimize application performance and resolve issues across different platforms.
- You hold a Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field.
- Proven 3+ years of experience as a Machine Learning Engineer or AI Developer in building complex AI-driven applications.
- Proficient programming experience in Python, with hands-on knowledge of libraries such as scikit-learn, Numpy, Pandas, Langchain, LangGraph, TensorFlow, or PyTorch.
- Familiarity with building APIs (Application Programming Interfaces) and integrating third-party libraries.
- Understanding of AWS services for deploying FastAPI applications (e.g., Lambda, S3, ECS, SageMaker, StepFunctions) or Basic understanding of the Azure services.
- Familiarity with the Agile development lifecycle.
- Knowledge of version control tools such as Git and CI/CD processes using Jenkins or similar tools.
- Strong problem-solving and critical-thinking abilities.
- Strong communication skills to support engagement with various collaborators.
- Ability to work under pressure and adhere to tight deadlines.
- Capability to switch between different projects as needed (e.g., application development vs. AI/ML Research).
- Experience with backend integrations relevant to machine learning applications and data pipelines, such as AWS services (e.g., SageMaker, Lambda, S3, Step Function) or other cloud-based platforms (Azure).
- Understanding of standard methodologies for deploying and managing AI/ML models in production environments.
- Understanding of time series analysis techniques and familiarity with handling time-dependent data using libraries such as Sklearn, Pandas and NumPy, along with knowledge of leveraging LLMs for various natural language processing tasks and user interactions in AI applications.
- Prior experience with model testing and validation frameworks (e.g., MLflow, Pytest for Python) to ensure the robustness and reliability of machine learning solutions.
- Proficiency in data engineering practices, including data wrangling, cleaning, and preprocessing for machine learning tasks.
- Employees are eligible for Remote Working arrangements up to 2 days per week.
- Opportunities to work with a distributed team
- Opportunities to work on and lead a variety of innovative projects
- Medical benefits
- Time off/Paid holidays and parental leave
- Continual learning through the Learn@Siemens-Energy platform