AI/ML Developer, FL

Role : AI/ML Developer

Location: NYC and Sunrise, FL

Face to face Interview Must

Key skills- Langchain, Multiple Agent, Strong Python, Lang Graph, NoSQL database, Isolation Forest, LOF Ensemble model working experience

The Role

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 10+ 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.