Location: Jersey City, NJ
Job Description:
Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity apply your skills and have a direct impact on global business. You will be building production-grade AI, Agentic workflows, ML services, developing end-to-end AI/ML pipelines, and collaborating to develop large-scale data modeling experiments. Your expertise in Python, PySpark, Knowledge Graphs, RAG, Vector stores, DL frameworks like TensorFlow, and MLOps will be crucial in this role.
As a senior software engineer with python, Lang chain, Lang graph , ai/ml engineering experience. Someone who has built some agentic applications.
Job responsibilities
Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases.
Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives.
Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
Conduct thorough evaluations of generative models (e.g., GPT-4.1), iterate on model architectures, and implement improvements to enhance overall performance in NLP applications.
Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
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Required qualifications, capabilities, and skills
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
6-9 years of demonstrated experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs.
Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications.
Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
A portfolio showcasing successful applications of generative models in NLP projects, including examples of utilizing OpenAI APIs for prompt engineering.
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