W2 Machine Learning Engineer

Machine Learning Engineer

W2- NO SPONSORSHIP AVAILABLE 

Overview: 

We are seeking a forward-thinking Machine Learning Engineer to evaluate and integrate emerging and start-up Artificial Intelligence (AI) and Machine Learning (ML) solutions that drive value. 

This role blends deep technical expertise in AI and ML with a passion for experimentation, creativity, and solving complex problems in novel ways. 

This position is part of the Mechatronics and Digital Labs Team responsible for providing thought leadership and execution of technology trials of emerging technologies to validate value and technical capability. 

The function of this role is to partner with the business to identify disruptive and emerging technologies to achieve greater business value faster. 

Our team is highly technical, creative, and innovative, and we are cross-functional and passionate about delivering creative solutions that drive significant business value. 

We are looking for a Machine Learning Engineer with the ability to bring expertise, an innovative attitude, and excitement for solving complex problems with new technologies and approaches. 

There will be no shortage of opportunities to lead, innovate, challenge the status quo, and work directly with Data Scientists, Analytics Professionals, and Business experts to build and deliver innovative, value-driven AI solutions.

Responsibilities:

• Partner with Digital Innovation teams to evaluate and test emerging AI and machine learning technologies
• Explore and experiment with Generative AI (GenAI), NLP, and computer vision applications
• Stay current with the latest AI advancements and integrate them into projects
• Collaborate with data scientists, data engineers, and solution architects across business units and IT
• Build and maintain robust data pipelines using platforms such as Databricks
• Deploy models in production using Docker and cloud platforms (AWS, Azure)
• Conduct machine learning experiments to validate hypotheses and improve performance
• Identify and frame AI opportunities to improve workflows, decision-making, and automation
• Define data, technologies, and architecture patterns to solve business challenges
• Transform data science prototypes into scalable production solutions
• Orchestrate infrastructure for low-latency, scalable, and resilient ML workloads
• Run experiments and fine-tune algorithms for optimal performance
• Participate in Agile teams to support cross-training and continuous improvement
• Continuously learn new technologies and design patterns to improve AI solution delivery

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Mathematics, or related field (or equivalent experience)
• 5+ years of experience in software engineering
• Strong Python development experience including data structures, OOP, and control flow
• Experience with ML frameworks and libraries (MLflow, Kubeflow, TensorFlow, Keras, scikit-learn, PyTorch, NumPy, SciPy)
• Experience with JavaScript frameworks (Angular, React, Node.js)
• Experience building ML pipelines in Microsoft Azure Machine Learning
• Experience developing cloud-first solutions using Azure services (Functions, App Services, Event Hubs, SQL DB, Synapse)
• Strong understanding of design patterns and ability to communicate design ideas
• Methodical, structured approach to building scalable software components
• Working knowledge of linear algebra, probability, statistics, and algorithms
• Experience with data engineering tools such as Databricks, Spark, and Azure Data Factory

Preferred Qualifications:

• Master’s degree in Computer Science, Mathematics, or related field
• Strong background in statistics and time-series analysis
• Experience orchestrating large-scale ML/DL workloads using Kubernetes or similar tools
• Experience designing APIs for ML training and inference
• Experience building and delivering MLOps frameworks
• Experience with unstructured data, cognitive services, and computer vision solutions
• Experience with model optimization and hyperparameter tuning
• Hands-on experience with Azure ML SDK deployments
• Strong Python debugging and OOP skills
• Strong architectural design skills and framework development experience
• Passion for high-quality software development practices
• Knowledge of enterprise SaaS requirements (security, scalability, availability, CI/CD, etc.)
• Strong understanding of software engineering best practices (version control, testing, architecture review)
• Proven ability to lead cross-functional projects in Agile environments
• Experience collaborating with data scientists to deploy advanced analytics solutions

Critical Selection Criteria:

• Technical Capability: Strong software engineering background with ML frameworks, mathematical knowledge, and ability to quickly learn new technologies to deliver AI solutions
• Business Engagement: Ability to partner with stakeholders to identify and implement machine learning solutions that drive business value
• Domain Knowledge: Experience in upstream, midstream, or downstream environments with ability to build cross-functional partnerships and deliver scalable AI solutions
• Communication: Strong verbal and written communication skills with the ability to clearly convey complex ideas and actively listen to stakeholders