Staff AI Engineer

Method is a global design and engineering consultancy founded in 1999. We believe that innovation should be meaningful, beautiful and human. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams [based in New York, Charlotte, Atlanta, London, Tokyo, Bengaluru, and remote] work with a wide range of organisations in many industries, including Healthcare, Financial Services, Retail, Automotive, Aviation, and Professional Services.

Method is part of Hitachi Digital, a digital product engineering company. Hitachi Digital integrates experience design and complex engineering to help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses. Hitachi Digital is a Hitachi Group Company.

Your role is to collaborate with multidisciplinary individuals and support the project lead on customer experience strategy, product design, data strategy, and business strategy projects. You will be responsible for building data analytics and predictive & prescriptive models that support various business initiatives from personalisation engines to suggestive product analytics insights and tailored marketing campaigns.

We pride ourselves on our user first approach to data science and analytics. We begin every project with an extended discovery phase designed to gain a deep and rich understanding of the problem we are solving for, the needs of end users, and the intricacies of the industry and business we are working within. You must have strong empathetic skills, and be able to diagnose and understand pain points.

At Method, we strive to work in a collaborative and supportive environment, and we look for people who can work flexibly and enjoy working as part of a team. Strategic thinking and creative problem solving are key skills to have at Method, as well as the love of continuously learning and sharing knowledge / mentoring team members and colleagues.

Responsibilities

Lead or co-lead data and AI engagements end to end, taking ownership of the quality of data deliverables and the structure of the work.

Combine design thinking and user-centric techniques with quantitative analysis to diagnose, define and design data-led products and services.

Facilitate technical discovery sessions and workshops with clients to uncover pain points, opportunities and available data sources.

Design and build predictive and prescriptive ML models, from personalisation and recommendation engines to lead scoring, CLTV, forecasting and risk detection.

Design and prototype GenAI and LLM solutions (RAG, agentic workflows, summarisation) that are secure, compliant and grounded in real user needs.

Build BI dashboards and data products, and define the KPIs and analytics layers that track adoption and outcomes.

Develop data strategies, data-to-decision mappings and phased roadmaps that connect business objectives to technical delivery.

Present work to client stakeholders up to C-suite and board level, using a highly visual approach that engages non-technical audiences.

Write clear documentation and handovers so clients can take solutions into production.

Support sales pursuits by scoping projects, writing proposals and SOWs, and building rapid POCs that prove value and feasibility.

Champion best practice in MLOps, cloud architecture and code quality, and review the work of other Data Designers.

Mentor junior Data Designers, interns and residency members, and contribute to onboarding materials.

Qualifications

4+ years in data science, ML engineering or data consulting, including leading client-facing projects.

Proven experience designing and deploying ML models that predict customer needs and behaviours, such as personalisation, recommendation, lead scoring, CLTV or churn and risk models.

Knowledge of recommendation and personalisation techniques: collaborative and content-based filtering, matrix factorisation, embeddings, contextual and UI personalisation.

Hands-on experience with LLMs and GenAI: prompt design, RAG, vector databases, and frameworks such as LangChain/LangGraph or Hugging Face.

Strong Python and SQL, with working knowledge of the wider ML stack (pandas, scikit-learn, PyTorch or TensorFlow, XGBoost).

Experience with cloud data and ML platforms, ideally AWS (S3, SageMaker Pipelines, Glue) and/or GCP, and MLOps practices (MLflow, CI/CD, Docker, infrastructure as code).

Ability to build BI dashboards (Power BI or Tableau) and quick, visual prototypes (for example Streamlit or React).

Excellent written, verbal and visual communication, with experience presenting to senior, non-technical stakeholders.

Confident running workshops and discovery sessions and turning ambiguous problems into clear scope.

Desirable Experience

Experience in pre-sales: scoping, proposal and SOW writing, and building POCs.

Experience with agentic AI, NLP, forecasting, Monte Carlo simulation or reinforcement learning.

Data engineering exposure: Airflow, Spark, Snowflake, PostgreSQL, MongoDB.

Experience hiring and mentoring, or contributing to a growing team's tooling and ways of working.

Domain experience in one or more of healthcare, financial services, retail, automotive, energy or EdTech.

A STEM degree or equivalent practical experience.

Location

Remote First with occasional need to travel to the London office.

Why Method?

We look for individuals who are smart, kind and brave. Curious people with a natural ability to think on their feet, learn fast, and develop points-of-view for a constantly changing world find Method an exciting place to work. Our employees are excited to collaborate with dispersed and diverse teams that bring together the best in thinking and making. We champion the ability to listen, and believe that critique and dissonance lead to better outcomes. We believe everyone has the capacity to lead and look for proactive individuals who can take and give direction, lead by example, enjoy the making as much as they do the thinking, especially at senior and leadership levels.

We believe in work/life balance. Seriously. We offer a ton of competitive perks, including:

Continuing education opportunities

Flexible PTO and work-from-home policies

Pension

Health and dental benefits

Company lunches, company outings, along with a lot of snacks

Health and wellness programs

Other location specific perks (just ask!)

Next Steps

If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a portfolio, GitHub, Dribbble or other platform.

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