Lead Machine Learning Engineer

Position Overview:

• We are seeking a highly skilled and experienced Lead/ Senior Machine Learning Engineer with expertise in Python and hands-on experience designing innovative solutions using Agentic systems and modeling large language models (LLMs).
• The ideal candidate will hold an Azure Certified AI Practitioner certification and demonstrate deep knowledge of Azure’s AI services and data engineering tools.

Key Responsibilities:

AI and Agentic Solutions Development:

Design, develop, and implement agentic systems for real-time decision-making processes.

Integrate multimodal AI agents capable of proactive problem-solving using machine learning and automation.

Collaborate with stakeholders to architect solutions that align with organizational goals.

LLM Development and Optimization:

Build, customize, and fine-tune large language models (LLMs) for diverse business applications.

Research and experiment with LLM architectures to optimize performance for specific use cases like NLP, conversational AI, and summarization.

Deploy LLMs efficiently on Azure services such as Azure Machine Learning, OpenAI Service, and Cognitive Services.

Data Engineering Expertise:

Architect and maintain complex data pipelines and frameworks on Azure.

Work with relational and non-relational databases to preprocess and manage datasets for AI models.

Leverage Azure tools like Data Factory, Synapse Analytics, and Databricks for ETL processes and advanced analytics workflows.

Python Development and Software Engineering:

Write high-quality, scalable Python code for machine learning and data engineering applications.

Develop reusable libraries for AI models and data processing workflows.

Collaborate with DevOps teams to ensure robust CI/CD pipelines and deploy production-ready solutions in cloud environments.

Collaboration and Leadership:

Mentor and guide junior engineers on best practices in data engineering and machine learning.

Collaborate with cross-functional teams, including data scientists, product managers, and business analysts.

Proactively contribute to strategic roadmaps for AI-powered business solutions.

Required Qualifications:

Azure Certified AI Practitioner (or equivalent Azure certification in AI and data engineering).

Demonstrable expertise in Python, with advanced knowledge of libraries such as Pandas, NumPy, PyTorch, TensorFlow, and LangChain.

Extensive experience designing and building Agentic solutions (e.g., autonomous agents capable of advanced decision-making and orchestration).

Hands-on experience with modeling and deploying LLMs (fine-tuning, prompt engineering, optimization).

Proficiency with Microsoft Azure ecosystem, including services like Azure Machine Learning, OpenAI Service, Cognitive Services, and Databricks.

Strong understanding of machine learning, natural language processing (NLP), and generative AI concepts.

Familiarity with best practices in data engineering, such as data modeling, schema design, ETL processes, and pipeline optimization.

Preferred Qualifications:

Advanced degree (Master’s or PhD) in Computer Science, Data Engineering, AI/ML, or a related field.

Experience with integrating LLMs into production environments for real-world applications (e.g., chatbots, document summarization, generative design).

Knowledge of distributed computing frameworks (e.g., Spark, Hadoop).

Familiarity with versioning tools (e.g., Git), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).