Managing Machine Learning Engineer

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Toyota Connected’s Mobility team is looking for a Managing Machine Learning Engineer capable of using machine learning and statistical techniques to create state‑of‑the‑art solutions for non‑trivial, unsolved problems. If you are results‑driven, interested in applying advanced Machine Learning techniques, love working with vehicle telemetry data and video, are deeply technical, highly innovative, and eager to build solutions that directly impact the company's bottom‑line, we want to talk to you.

• Use statistical and machine learning techniques to create scalable solutions for in‑vehicle speech and text interactions and perform R&D to drive discovery of new generation products.
• Establish scalable, efficient, automated processes for large‑scale data analysis, model development, model validation and model implementation.
• Drive engineering and product strategy, vision, and roadmaps working closely with product owners and customers.
• Regularly dive into architecture, code, deployments, and operations to model technical excellence for the team.
• Manage feature backlogs in partnership with product owners and key stakeholders.
• Define and set standards for engineering rigor and help cultivate an engineering‑driven culture.
• Influence best practices in product management, software development, and CI/CD methodologies.
• Align technical resourcing to product release plans and material plans; drive programs to completion on time and within budget.
• Manage staffing, development, and performance management for engineering teams; motivate and develop project and team leaders.
• Lead, develop, train, mentor and provide coaching and guidance to engineering staff.
• Facilitate team growth by attracting candidates, interviewing, evaluating, and selecting new talent.
• Take full ownership of your team’s outcomes — from delivering reliable systems to resolving technical debt and driving continuous improvement, even in areas outside your immediate scope.

• 5+ years of software engineering, machine learning, data science, or total equivalent experience.
• Experience working with deployment and monitoring of ML models in a production cloud‑based containerized environment.
• Ability to write clean, concise, tested, maintainable code in Python.
• Experience with Deep Learning areas such as computer vision, NLP, or ANN.
• Understanding of how Deep Learning areas work and how to implement them using PyTorch or Tensor Flow.
• Experience with designing, implementing, and maintaining machine learning pipelines in a production environment.
• Experience in Agile practices and promoting Agile development techniques such as TDD, BDD and CI/CD.
• Experience with public cloud including AWS, Azure, or GCP.
• Proven experience building, leading, and developing high‑performing teams, including hiring, mentoring, and performance management.
• Ability to foster collaboration and drive cross‑functional teamwork.
• Experience conducting regular performance reviews, providing actionable feedback, and driving continuous improvement.
• Ability to track engineering team performance against objectives, ensuring accountability and high‑quality results.
• Ability to adjust strategies and priorities in response to changing business and technical needs.
• Ability to persuade and gain buy‑in from stakeholders at all levels.
• Strong analytical and problem‑solving skills to overcome complex technical and team challenges.
• Skilled at addressing and resolving interpersonal and team conflicts constructively and effectively.

Excited about this opportunity, but don't meet 100% of the qualifications? We’d still love for you to apply! Toyota Connected is dedicated to building a diverse and inclusive workplace where unique experiences are valued, and everyone has the opportunity to contribute. You may just be the right candidate for this, or other Toyota Connected opportunities.

This position is based in Plano, Texas. Toyota Connected encourages all employees to live within a reasonable commuting distance of their assigned work location for hybrid work.

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