Leading the design, development, and deployment of AI/ML models for remote diagnostics, predictive maintenance, and operational optimization.
Analyzing large-scale machine and service datasets to uncover actionable insights and inform product improvements.
Collaborating with cross-functional teams including engineering, product management, and MLOps to integrate AI solutions into commercial applications.
Appling statistical, machine learning, and optimization techniques to solve complex healthcare challenges.
Developing and operationalizing GenAI solutions, including RAG architectures and AI agents using AWS, Azure, and open-source tools.
Ensuring scalability, reusability, and high-quality standards across AI products and pipelines.
Communicating technical findings and strategic recommendations to stakeholders across business and technical domains.
Mentoring junior team members and promote a culture of data-driven decision-making and continuous learning.

Requirements

M.S. or Ph.D. in Computer Science, Data Science, Engineering, or a related STEM field
Advanced experience in AI/ML development, with a strong portfolio of deployed models
Experience in diagnostics/prognostics, system health monitoring, and reliability engineering
Strong foundation in applied analytics, statistical modeling, and feature engineering
Skilled in data cleaning, data quality assessment, and exploratory data analysis
Proficiency in Python and data science tools (e.g., Jupyter, Scikit-learn, TensorFlow, PyTorch)
Experience with cloud platforms (e.g., AWS) and big data technologies (e.g., Spark)
Hands-on experience with deep learning architectures (CNNs, RNNs, GANs)
Familiarity with GenAI tools (e.g., AWS Bedrock) and RAG models
Knowledge of cloud-native AI development and deployment practices
Experience in healthcare or industrial AI applications
Ability to translate business needs into technical solutions
Awareness of industry trends and emerging technologies
Proven ability to lead projects and mentor team members
Strong communication and stakeholder engagement skills
Results-driven with a collaborative mindset
Strong problem-solving and critical thinking abilities
Effective communicator with a passion for innovation and continuous improvement.

Benefits

Health & wellness coverage
Retirement and or savings plans
Allowances or benefits to support role requirements (e.g., mobility, transport, or role-specific needs such as a company car or allowance where applicable)
Work-life balance support (e.g., flexible working, leave programs)
Recognition and incentive programs aligned with performance and company success

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI developmentML developmentstatistical modelingfeature engineeringdata cleaningdata quality assessmentexploratory data analysisdeep learning architecturesGenAI solutionspredictive maintenance

Soft Skills

mentoringcommunicationstakeholder engagementproblem-solvingcritical thinkingcollaborationresults-drivendata-driven decision-makingcontinuous learninginnovation

Certifications

M.S. in Computer SciencePh.D. in Computer ScienceM.S. in Data SciencePh.D. in Data ScienceM.S. in EngineeringPh.D. in Engineering