Lead Machine Learning Engineer (Locals to NJ Preferred) - W2 Role

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Machine Learning Engineer in Weehawken, NJ, on a W2 contract for an unspecified duration, offering competitive pay. Key skills include Python, Azure AI services, LLM development, and data engineering expertise. Azure Certified AI Practitioner required.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
August 22, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
On-site
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πŸ“„ - Contract type
W2 Contractor
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Weehawken, NJ
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Spark (Apache Spark) #Data Science #NumPy #NLP (Natural Language Processing) #Pandas #Data Pipeline #TensorFlow #Business Analysis #Computer Science #Langchain #Schema Design #Libraries #Data Engineering #Distributed Computing #Docker #Scala #"ETL (Extract #Transform #Load)" #ML (Machine Learning) #Hadoop #GIT #Data Processing #Data Modeling #Automation #Synapse #Azure #Kubernetes #DevOps #Leadership #Azure Machine Learning #PyTorch #Databases #Databricks #Datasets #Cloud #Microsoft Azure #Python
Role description
Role: Lead / Senior Machine Learning Enginee Location: Weehawken, NJ (Day 1 Onsite) - Locals preferred Job Type: W2 Contract Position Overview β€’ 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). β€’ 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: β€’ Design, develop, and implement agentic systems for real-time decision-making processes. β€’ Integrate multimodal AI agents capable of proactive problem-solving using machine learning and automation. β€’ Collaborate with stakeholders to architect solutions that align with organizational goals. LLM Development And Optimization β€’ Build, customize, and fine-tune large language models (LLMs) for diverse business applications. β€’ Research and experiment with LLM architectures to optimize performance for specific use cases like NLP, conversational AI, and summarization. β€’ Deploy LLMs efficiently on Azure services such as Azure Machine Learning, OpenAI Service, and Cognitive Services. Data Engineering Expertise β€’ Architect and maintain complex data pipelines and frameworks on Azure. β€’ Work with relational and non-relational databases to preprocess and manage datasets for AI models. β€’ Leverage Azure tools like Data Factory, Synapse Analytics, and Databricks for ETL processes and advanced analytics workflows. Python Development And Software Engineering β€’ Write high-quality, scalable Python code for machine learning and data engineering applications. β€’ Develop reusable libraries for AI models and data processing workflows. β€’ Collaborate with DevOps teams to ensure robust CI/CD pipelines and deploy production-ready solutions in cloud environments. Collaboration And Leadership β€’ Mentor and guide junior engineers on best practices in data engineering and machine learning. β€’ Collaborate with cross-functional teams, including data scientists, product managers, and business analysts. β€’ Proactively contribute to strategic roadmaps for AI-powered business solutions. Required Qualifications β€’ Azure Certified AI Practitioner (or equivalent Azure certification in AI and data engineering). β€’ Demonstrable expertise in Python, with advanced knowledge of libraries such as Pandas, NumPy, PyTorch, TensorFlow, and LangChain. β€’ Extensive experience designing and building Agentic solutions (e.g., autonomous agents capable of advanced decision-making and orchestration). β€’ Hands-on experience with modeling and deploying LLMs (fine-tuning, prompt engineering, optimization). β€’ Proficiency with Microsoft Azure ecosystem, including services like Azure Machine Learning, OpenAI Service, Cognitive Services, and Databricks. β€’ Strong understanding of machine learning, natural language processing (NLP), and generative AI concepts. β€’ Familiarity with best practices in data engineering, such as data modeling, schema design, ETL processes, and pipeline optimization. Preferred Qualifications β€’ Advanced degree (Master’s or PhD) in Computer Science, Data Engineering, AI/ML, or a related field. β€’ Experience with integrating LLMs into production environments for real-world applications (e.g., chatbots, document summarization, generative design). β€’ Knowledge of distributed computing frameworks (e.g., Spark, Hadoop). β€’ Familiarity with versioning tools (e.g., Git), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).