AI/ML Engineer

This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world. Our culture thrives on finding new and better ways to accelerate what's next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description
HPE Operations
is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers' outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today's fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what's next for you.

What You'll Do
We are seeking an experienced
AI / ML Engineer
with 7+ years of expertise in designing, developing, and deploying
machine learning and artificial intelligence solutions
at enterprise scale. The ideal candidate will build scalable ML pipelines, apply deep learning and advanced analytics, and collaborate with data scientists and engineers to transform business problems into intelligent, data-driven solutions.

Key Responsibilities

• Model Development & Deployment

• Design, train, and optimize ML/DL models for classification, prediction, NLP, computer vision, and recommendation systems.

• Deploy ML models into production using MLOps frameworks (Kubeflow, MLflow, SageMaker, Vertex AI, Azure ML).

• Develop reusable ML components for scalability and automation.

• Data Engineering for ML

• Work with large-scale datasets for feature extraction, cleaning, and transformation.

• Implement data pipelines for real-time and batch ML workloads.

• Ensure data quality, consistency, and lineage across pipelines.

• MLOps & Automation

• Build end-to-end automated ML lifecycle pipelines (training, testing, deployment, monitoring).

• Integrate CI/CD practices into ML model deployment.

• Implement drift detection, continuous learning, and retraining strategies.

• Performance & Optimization

• Optimize algorithms for speed, accuracy, and cost efficiency.

• Leverage GPU/TPU environments for high-performance training.

• Benchmark models and fine-tune hyperparameters for business KPIs.

• Security & Governance

• Ensure compliance with ethical AI practices and regulatory frameworks.

• Implement security measures for ML models (adversarial robustness, secure APIs).

• Collaborate with cybersecurity and governance teams for responsible AI adoption.

• Collaboration & Innovation

• Work with data scientists, data engineers, and business analysts to align AI solutions with business outcomes.

• Mentor junior engineers and contribute to best-practice frameworks.
• Stay updated on emerging AI/ML research, tools, and technologies.

What You Need To Bring
Required Skills & Experience

• 7+ years in AI/ML engineering, data science, or applied machine learning.
• Proficiency in Python, R, or Scala with ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost).
• Strong background in statistics, data mining, and algorithm design.
• Hands-on experience with cloud AI/ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
• Familiarity with MLOps tools (Kubeflow, MLflow, Airflow, Docker, Kubernetes).
• Strong knowledge of SQL/NoSQL databases and data lakes.

Preferred Knowledge

• Experience with Generative AI (LLMs, diffusion models, transformers).
• Domain knowledge in NLP, CV, or reinforcement learning.
• Exposure to streaming data ML (Kafka, Flink, Spark Streaming).
• Familiarity with responsible AI frameworks (Fairness, Explainability, Bias detection).

Education & Certifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.

• Preferred certifications:

• AWS Certified Machine Learning – Specialty / Azure AI Engineer Associate / GCP ML Engineer.

• TensorFlow or PyTorch professional certifications.

Additional Skills
Accountability, Accountability, Active Learning, Active Listening, Bias, Business Growth, Client Expectations Management, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Customer Centric Solutions, Customer Relationship Management (CRM), Design Thinking, Empathy, Follow-Through, Growth Mindset, Information Technology (IT) Infrastructure, Infrastructure as a Service (IaaS), Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity, Process Improvements, Product Services, Relationship Building {+ 5 more}

What We Can Offer You
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

Job
Services

Job Level
TCP_02

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.