Compunnel
Job Summary
We are seeking a highly skilled and motivated AI/ML Engineer to design, develop, and deploy machine learning models and AI-driven solutions that address real-world challenges and deliver measurable business impact.
This role requires a strong foundation in data science, machine learning engineering, and software development, along with a passion for innovation and problem-solving.
Key Responsibilities Design and implement machine learning models for tasks such as classification, regression, clustering, recommendation systems, natural language processing (NLP), and computer vision. Collaborate with data scientists, software engineers, and product teams to integrate ML models into production environments. Build and maintain scalable data pipelines and model training workflows. Conduct experiments, evaluate model performance, and iterate to improve accuracy, efficiency, and robustness. Stay current with advancements in AI/ML and apply relevant innovations to ongoing projects. Optimize models for performance, scalability, and interpretability. Document processes, models, and systems to ensure reproducibility and facilitate knowledge sharing. Required Qualifications
Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field. 8+ years of experience developing and deploying machine learning models and AI solutions. 5+ years of programming experience in Python, with expertise in ML libraries such as TensorFlow, PyTorch, and Scikit-learn. 5+ years of experience with core machine learning algorithms, data structures, and statistical modeling techniques. 3+ years of experience using cloud platforms (AWS, GCP, Azure) for AI/ML deployment, including familiarity with ML Ops tools (e.g., SageMaker, Vertex AI, Azure ML). Exposure to data engineering tools such as Apache Spark, Airflow, or Kafka (preferred). Strong analytical thinking, problem-solving, and communication skills. Preferred Qualifications
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. Experience deploying models in real-time inference systems or on edge devices. Prior experience working with healthcare data architectures or Health Plan applications.
Education:
Bachelors Degree
We are seeking a highly skilled and motivated AI/ML Engineer to design, develop, and deploy machine learning models and AI-driven solutions that address real-world challenges and deliver measurable business impact.
This role requires a strong foundation in data science, machine learning engineering, and software development, along with a passion for innovation and problem-solving.
Key Responsibilities Design and implement machine learning models for tasks such as classification, regression, clustering, recommendation systems, natural language processing (NLP), and computer vision. Collaborate with data scientists, software engineers, and product teams to integrate ML models into production environments. Build and maintain scalable data pipelines and model training workflows. Conduct experiments, evaluate model performance, and iterate to improve accuracy, efficiency, and robustness. Stay current with advancements in AI/ML and apply relevant innovations to ongoing projects. Optimize models for performance, scalability, and interpretability. Document processes, models, and systems to ensure reproducibility and facilitate knowledge sharing. Required Qualifications
Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field. 8+ years of experience developing and deploying machine learning models and AI solutions. 5+ years of programming experience in Python, with expertise in ML libraries such as TensorFlow, PyTorch, and Scikit-learn. 5+ years of experience with core machine learning algorithms, data structures, and statistical modeling techniques. 3+ years of experience using cloud platforms (AWS, GCP, Azure) for AI/ML deployment, including familiarity with ML Ops tools (e.g., SageMaker, Vertex AI, Azure ML). Exposure to data engineering tools such as Apache Spark, Airflow, or Kafka (preferred). Strong analytical thinking, problem-solving, and communication skills. Preferred Qualifications
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. Experience deploying models in real-time inference systems or on edge devices. Prior experience working with healthcare data architectures or Health Plan applications.
Education:
Bachelors Degree