AI ML Engineer/Architect in Remote

• Prior experience working with Health Plan applications and healthcare data architectures is required.
• This position would require candidates with data engineering background who are extensively working in AI/ML space for last 4-5 years, that too in health plan domain.

• We are seeking a highly skilled and motivated Machine Learning / AI Engineer to join our team. You will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions that solve real-world problems and drive measurable business value. This role requires a strong foundation in data science, machine learning engineering, and software development, along with a passion for innovation and problem-solving.

• Design and implement machine learning models for classification, regression, clustering, recommendation, NLP, or computer vision tasks.
• Collaborate with data scientists, software engineers, and product teams to integrate ML models into production systems.
• Build and maintain scalable data pipelines and model training workflows.
• Conduct experiments, evaluate model performance, and iterate to improve accuracy, efficiency, and robustness.
• Stay up to date with the latest research and advancements in AI/ML and apply them to relevant projects.
• Optimize models for performance, scalability, and interpretability.
• Document processes, models, and systems to ensure reproducibility and knowledge sharing.

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• 8+ years of experience in developing and deploying machine learning models and AI solutions in real-world environments.
• 5+ years of experience programming in Python, with expertise in ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• 5+ years of experience working with core machine learning algorithms, data structures, and statistical modeling techniques.
• 3+ years of experience using cloud platforms (AWS, GCP, Azure) for building and deploying AI/ML solutions, including familiarity with ML Ops tools (e.g., SageMaker, Vertex AI, Azure ML).
• 2+ years of experience or exposure to data engineering tools such as Apache Spark, Airflow, or Kafka (preferred but not mandatory).
• Strong problem-solving, analytical thinking, and communication skills with the ability to translate complex concepts into practical applications.

• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Experience with deep learning, reinforcement learning, or generative AI (e.g., GANs, LLMs).
• Contributions to open-source ML/AI projects or published academic research papers.
• Experience deploying models in real-time inference systems or on edge devices.
• Prior experience working with Health Plan applications and healthcare data architectures is a strong plus.

TechnoGen