Job description

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.

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