Senior Machine Learning Operations Engineer
2 days ago
Mendel is a pioneering organization at the forefront of revolutionizing the healthcare industry through cutting-edge AI and technology. Our mission is to harness the power of clinical data and deliver actionable insights that drive better patient outcomes. At Mendel, we believe in the potential of AI to transform the healthcare industry by providing solutions that are not just faster but more intelligent and reliable. Our comprehensive clinical intelligence platform, Hypercube, combines advanced machine learning with deep clinical understanding to deliver precise, actionable insights from complex data sets.
Role OverviewWe are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. In this role, you will design, develop, and deploy machine learning models, including Large Language Models (LLM), that enhance our AI-powered clinical intelligence platform. You will work closely with researchers, engineers, and clinical experts to create innovative solutions that drive our mission forward.
Key Responsibilities- Develop and Implement Scalable AI and Machine Learning Models: Design, develop, and deploy scalable and reliable AI and machine learning models and algorithms to enhance our clinical intelligence platform.
- Accelerate Product Development: Enable the research and AI development to accelerate overall product development by implementing efficient machine learning pipelines.
- Design and Build Services and Tools: Design and build services, tools, and platforms to support the growth of our clinical intelligence platform.
- Collaborate with Experts: Collaborate with engineering, AI, and clinical experts to understand the intricacies of healthcare data and refine model performance.
- Design and Execute Experiments: Design and execute experiments to test the efficacy of new models and algorithms.
- Deploy and Maintain Models: Deploy and maintain machine learning and AI models in a production environment, ensuring scalability and reliability.
- Monitor and Optimize Model Performance: Continuously monitor and optimize the performance of deployed models.
- Stay Updated with Latest Advancements: Stay updated with the latest advancements in machine learning and AI, and incorporate new techniques and tools as appropriate.
- Contribute to Best Practices: Participate in code reviews and contribute to developing best practices for machine learning at Mendel.
- Education: Bachelor's or Master's in Computer Science, Machine Learning, Data Science, or a related field.
- Experience: 5+ years of experience in building AI/ML training and inference pipelines using MLFlow, Kubeflow in GCP, AWS, and/or Azure.
- Machine Learning Expertise: Proven experience in developing and deploying machine learning models.
- Programming Skills: Proficiency in programming languages such as Python, R, or Java.
- ML and AI Algorithms: Proven experience in ML, AI algorithms, model tuning, and optimization.
- Machine Learning Frameworks: Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
- Data Preprocessing and Feature Engineering: Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Cloud Infrastructure: Proficiency in cloud infrastructure is a plus.
- Healthcare Data and Clinical Expertise: Familiarity with healthcare data and clinical expertise is a plus.
- Problem-Solving and Communication Skills: Excellent problem-solving skills and attention to detail, with strong communication and interpersonal skills, and the ability to convey complex technical concepts to non-technical stakeholders.
- Competitive Salary and Benefits: Competitive salary and benefits package.
- Opportunity to Work with a Talented Team: Opportunity to work with a talented and passionate team at the cutting edge of AI and healthcare.
- Collaborative Work Environment: Collaborative and inclusive work environment that values creativity and innovation.
- Professional Development Opportunities: Professional development opportunities and support for continuous learning.
- Meaningful Impact: The chance to make a meaningful impact on the healthcare industry and improve patient outcomes.
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