Scientist 4, Data Science

Company Description

WD is building the infrastructure behind the AI-driven data economy.

As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time. That’s where we come in.

We combine deep engineering expertise with global-scale manufacturing to deliver the storage systems that make AI possible, powering hyperscale data centers, cloud platforms, and enterprise infrastructure worldwide.

This isn’t theoretical work. It’s real systems, at real scale, people solving some of the hardest challenges in technology today.

We’re looking for people who want to build, solve, and operate at that level.

Join us and let’s shape the future of data.

Job Description

Key Responsibilities

Technical Leadership & Program Ownership

Lead the end-to-end design, architecture, and implementation of large-scale machine learning programs involving multiple interconnected projects

Own the technical vision and roadmap for ML initiatives across the organization, ensuring alignment with business objectives

Drive solutioning efforts for complex, ambiguous problems by breaking them down into actionable technical components

Establish best practices, design patterns, and architectural standards for ML systems at scale

Make critical technical decisions on model selection, infrastructure, tooling, and deployment strategies

Champion production excellence by ensuring ML systems are reliable, scalable, maintainable, and cost-efficient

Goals & Metrics Ownership

Define success metrics and KPIs for ML initiatives, establishing clear linkage between technical work and business outcomes

Drive a metrics-driven culture by implementing comprehensive monitoring, experimentation frameworks, and impact measurement systems

Analyze and communicate the business impact of ML solutions through rigorous A/B testing and causal inference methodologies

Set and track ambitious yet achievable goals for your programs, proactively identifying and mitigating risks

Translate business objectives into quantifiable ML objectives and success criteria

Mentorship & Team Development

Mentor and guide junior and mid-level data scientists and ML engineers, accelerating their technical growth and career development

Conduct code reviews, design reviews, and provide constructive feedback to elevate team quality standards

Foster a culture of technical excellence, innovation, and continuous learning within the team

Develop and deliver technical training sessions on advanced ML topics, tools, and methodologies

Help shape hiring standards and participate actively in recruiting top ML talent

Stakeholder Management & Communication

Build and maintain strong relationships with cross-functional partners including product managers, engineers, executives, and business stakeholders

Communicate complex technical concepts and results to non-technical audiences through compelling data storytelling

Present strategic recommendations and technical proposals to senior leadership and executive teams

Navigate organizational complexity to drive alignment and consensus across multiple stakeholders

Proactively manage expectations and communicate risks, tradeoffs, and dependencies clearly

Innovation & Research

Stay at the forefront of ML/AI research and identify opportunities to apply cutting-edge techniques to business problems

Publish findings through internal tech talks, external conferences, or academic papers (optional)

Drive innovation through rapid prototyping, experimentation, and willingness to challenge conventional approaches

Balance innovation with pragmatism, knowing when to leverage proven solutions versus exploring novel approaches

Qualifications

Education & Experience

PhD or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related quantitative field (or equivalent practical experience)

10+ years of hands-on experience in machine learning, data science, or related fields

4+ years of experience leading technical projects or programs with demonstrated business impact

Proven track record of deploying ML models/ LLM Agents to production at scale

Technical Expertise

Expert-level proficiency in machine learning frameworks (TensorFlow, PyTorch)

Deep understanding of ML fundamentals: supervised/unsupervised learning, deep learning, reinforcement learning, causal inference, optimization, and statistical modeling

Strong software engineering skills with proficiency in Python and experience with production-grade code development

Experience with knowledge graph integration, structured data extraction, or enterprise search systems

Extensive experience with ML infrastructure and MLOps: model serving, monitoring, experimentation platforms, feature stores, and model registry

Proficiency with big data technologies (Spark, Hadoop, distributed computing frameworks)

Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)

Strong understanding of algorithms, data structures, and system design principles

LLM & Agent Specialization:

Experience in specialized applications: conversational AI, code assistants, information extraction, content generation, or autonomous decision-making systems

Experience building complex multi-agent systems with inter-agent communication and coordination

Hands-on experience with instruction tuning, preference learning (RLHF/DPO), or continued pretraining of LLMs

Experience with LLM observability and monitoring tools (LangSmith, Weights & Biases, Phoenix, or similar)

Knowledge of emerging agent architectures and research (Tree of Thoughts, ReWOO, Reflexion, etc.)

Experience with code generation models and AI-assisted development tools

Familiarity with multimodal LLMs and vision-language models

Leadership & Soft Skills

Demonstrated ability to lead and influence without direct authority across organizational boundaries

Exceptional communication skills with ability to distill complex technical concepts for diverse audiences

Proven stakeholder management experience with senior leadership and cross-functional teams

Strong analytical and problem-solving skills with attention to detail and business acumen

Self-starter with ability to operate autonomously in ambiguous environments

Track record of mentoring and developing technical talent

Preferred Qualifications

Experience in one or more specialized domains: LLMs, NLP, computer vision, recommendation systems, time series forecasting, ranking, or LLMs/generative AI

Publications in top-tier conferences (NeurIPS, ICML, ICLR, KDD, CVPR, ACL, etc.) or journals

Experience building and scaling ML/LLM platforms or infrastructure

Background in experimentation design and causal inference methodologies

Contributions to open-source ML projects or communities

Experience working in high-growth technology companies or FAANG environments

Track record of patent filings or granted patents in ML/AI

Familiarity with ML model governance, fairness, and responsible AI practices specifically for generative AI

Additional Information

We are seeking an exceptional Principal ML Engineer to join our team as a technical leader who will drive innovation and excellence in machine learning at scale. In this role, you will lead the solutioning and execution of large, complex programs spanning multiple projects while establishing technical direction and mentoring the next generation of ML talent.

This is a high-impact role requiring a unique blend of deep technical expertise, strategic thinking, stakeholder management, and leadership capabilities. You will be responsible for translating ambiguous business challenges into concrete, metric-driven ML solutions that deliver measurable business value.

WD thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

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Notice To Candidates: Please be aware that WD and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately to WD Ethics Helpline or email compliance@wdc.com.