Senior Applied Machine Learning Engineer

Description

The company is an edge-to-cloud business that helps other organisations connect, protect, analyze and act on their data and applications, wherever they run.

This is an engineering role at job level TCP04, working with customers and cross-functional teams to deploy AI and machine learning solutions.

The ideal candidate has deployed and integrated ML and AI in real customer settings, either as part of a client-facing AI/ML solutions team or as an end user of AI/ML products.

Responsibilities

• Build and ship machine learning models and AI solutions for real customer problems, with attention to ease of use, scale and performance.
• Quickly produce demos, proofs of concept, MVPs and workflows that show new AI/ML capabilities for the product or for improving existing features based on customer feedback or market research.
• Test emerging techniques and tools, turning them into working prototypes that show practical value.
• Build and improve the integration of open-source ML/AI tools such as MLFlow, Spark, LangChain and Kubeflow into production systems that run reliably on Kubernetes.
• Tune models and algorithms for accuracy, efficiency and scale in production, including deep learning approaches.
• Turn customer needs and industry trends into AI/ML solutions that improve product features, data management and system performance.
• Work with product managers, data scientists and engineers to brainstorm, design and roll out solutions, and document procedures and best practices.
• Lead the adoption of new AI tools, mentor junior team members and report progress and challenges to leadership.

Requirements

• PhD with at least 2 years of relevant industry experience, or an equivalent: Master's with 4+ years, or Bachelor's with 6+ years.
• Extensive hands-on experience applying machine learning and AI in customer-facing or end-user environments.
• A proven record of deploying models to production with dependable reliability and performance.
• Experience with open-source ML/AI tools and frameworks.
• Backend programming in Python and Go.
• Ability to build, use and maintain AI agents, with proven experience coding agents for automation or decision-making.
• Strong written and verbal communication, especially for asynchronous collaboration.
• Experience with AI agents and automation.
• Knowledge of inference deployment and optimization techniques.
• Familiarity with large-scale data pipelines.
• Experience with retrieval-augmented generation (RAG) systems.

Conditions

Hybrid role, with an expectation of working in a company office on average 2 days per week.

Expected base salary for US roles in Georgia and North Carolina is $141,000 to $325,000 per year in USD, depending on location, experience, education and skill; variable incentives may also be offered.

The company is an equal opportunity employer that does not discriminate on protected characteristics, accommodates applicants with disabilities on request, and follows laws on arrest and conviction records.

Benefits

• Health and wellbeing support covering physical, financial and emotional wellbeing for team members and their families.
• Career development programs, including paths to becoming a subject expert or moving into another division.