AI / ML Engineer / Data Scientist

AI / ML Engineer / Data Scientist Jersey is the preference- hybrid (open to Boston / Mclean as well) CTH- must be eligible for conversion 2 rounds of interviews Will be converting at a senior associate level Experience with Agentic AI development. Summary We're seeking a passionate, hands‐on AI / ML Engineer to join our dynamic Technology Research and Innovation team, where you'll play a pivotal role in spearheading AI initiatives and innovation. As an AI / ML Engineer, you will play a pivotal role in designing, developing, and deploying Artificial Intelligence systems that solve complex problems and drive our technological advancement. Qualifications Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field. 6+ years of experience in Machine Learning and Data Science. Strong programming skills in Python Experience working with large datasets and performing data analysis. Experience with Machine Learning, Data Visualization, and Generative AI libraries and frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain). Experience in Prompt Engineering, LLM Fine Tuning, and evaluation techniques Proven experience in developing and deploying machine learning models in a production environment. Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic AI Workflow, Statistical methods, data structures, and algorithms. Experience with Snowflake Data Pipelines (stream, task, UDF) and Cortex features is a plus Experience with AWS Sage Maker, Bedrock, and AWS cloud platform for deploying AI solutions. Experience in building Asynchronous Python APIs for model inferencing. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. Previous experience in a similar role or industry is preferred. Excellent communication and collaboration skills. Strong problem‑solving skills and analytical thinking Passion for learning and staying up-to-date with the latest advancements in AI field Responsibilities Generative AI Application Development Develop and implement AI solutions such as Retrieval‑Augmented Generation (RAG) and Agentic AI Workflows using advanced techniques in prompt engineering and fine‑tuning of Large Language Models (LLMs). Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals. Collaborate with cross‑functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities. Model Development and Deployment Design and develop machine learning models and algorithms to address business challenges and improve product features. Deploy machine learning models in production environments to ensure scalability and efficiency. Optimize and refine models based on performance metrics and feedback. Data Management Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation. Implement data augmentation and feature engineering techniques to enhance model performance. Maintain and manage data pipelines to ensure seamless data flow and integration. Python API Development Develop scalable APIs in python (fastApi, Apache, Gunicorn, Uvicorn) for model inferencing Research and Innovation Stay updated with the latest trends and advancements in AI and machine learning technologies. Conduct research to explore new methodologies and techniques that can be applied to current and future projects. Collaborate with cross‑functional teams to drive innovation and implement cutting‑edge solutions. Collaboration and Communication Work closely with software engineers, data scientists, and product managers to align AI / ML initiatives with business goals. Communicate complex technical concepts and results to non‑technical stakeholders in a clear and concise manner. Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.s. #J-18808-Ljbffr