Lead Machine Learning Engineer; Locals to NJ - W2

Overview

Lead/ Senior Machine Learning Engineer role with onsite requirements in Weehawken, NJ. Local candidates preferred. This is a W2 contract position.

Location:

Weehawken, NJ (Day 1 Onsite) - Locals preferred

Job Type: W2 Contract

• 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.

• 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.

• 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.

• 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 Dev Ops teams to ensure robust CI/CD pipelines and deploy production-ready solutions in cloud environments.

• 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.

• 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, Num Py, PyTorch, Tensor Flow, and Lang Chain.
• 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.

• 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).