Lead Machine Learning Engineer

Main skill: Python, AI agents, LLM, Azure

Employment type: C2C

Project duration: 3 months

Location: Weehawken, NJ, USA (candidates who are open and ready to relocate)

Work mode: full-time, office

Travel: no travel

Recruitment process: General Interview - Technical Interview - Project Interview (30 min) Client interview

Required start date: Asap

Level: Lead/ Senior 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. As a critical member of our team, you will work to develop scalable data solutions, leverage cutting-edge AI technologies, and build intelligent systems that drive business innovation.

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).

Soft Skills:

• Strong problem-solving skills with the ability to think critically and innovate.
• Excellent communication skills to articulate complex technical concepts to non-technical stakeholders.
• Leadership and mentorship qualities to guide teams and ensure successful project delivery.
• Ability to thrive in a fast-paced, collaborative, and Agile work environment.