Position: AI/ML Developer Location: NYC and Sunrise, FL (client in person interview required look for only local candidate) Duration: 12 Months Contract/Permanent Role Key Skills : Langchain, Multiple Agent, Strong Python, Lang Graph, NoSQL database, Isolation Forest, LOF, Ensemble model working experience. Job Responsibilities: • Develop and implement AI/ML models: Design, develop, test, and deploy machine learning models that solve real-world problems. Candidate will handle data preprocessing, model training, tuning, and evaluation. • Data Exploration and Analysis: Work with structured and unstructured data to prepare it for ML models. Collaborate with data engineers to ensure high data quality and availability. • Model Optimization: Optimize algorithms to ensure high accuracy and low latency. Use techniques like hyperparameter tuning, regularization, and transfer learning. • Collaborate Across Teams: Work with product managers, engineers, and data scientists to integrate AI solutions into the company’s offerings. Provide technical expertise and share knowledge with team members. • Maintain and Update Models: Monitor the performance of deployed models, make improvements as needed, and ensure their reliability and scalability. • Stay Updated: Keep up with the latest AI/ML advancements, tools, and libraries to bring innovative approaches to the team. Requirements: You are: • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. • Minimum of 15+ years of experience in AI/ML model development, deployment, and optimization. • Proficiency in Python, R, or similar programming languages. • Experience with machine learning libraries like TensorFlow, PyTorch, Scikit-learn, etc. • Strong knowledge of ML algorithms, including supervised, unsupervised, and reinforcement learning. • Familiarity with cloud platforms (AWS, Azure, Google Cloud) for deploying models. • Understanding of data preprocessing techniques and experience with SQL and NoSQL databases. • Analytical Skills: Excellent problem-solving skills and a data-driven mindset. • Communication: Ability to explain technical concepts to non-technical stakeholders effectively. It would be great if you also had: • Experience with natural language processing, computer vision, or recommendation systems. • Familiarity with big data technologies (e.g., Spark, Hadoop) and data visualization tools. • Understanding of MLOps and experience with tools like MLflow or Kubeflow. • Knowledge of Agile methodologies.