Lead Machine Learning Engineer

Albuquerque, NM
30+ days ago

Job Description

Our client helps organizations globally to build trust and speed into their business by matching the Speed of PrivacyOps to the Speed of Dev/BusinessOps. Clients include Patreon, Twilio, Coinbase, Robinhood, and Samara.












Design and implement end-to-end Machine Learning and Natural Language Processing models and systems to help construct the foundation on which our global data infrastructure will be built.





Role Overview

















This role requires you to strategize and drive the execution of the core initiatives of the Machine Learning (ML) team. You are a Principal level individual contributor with a track record of successfully delivering machine learning models and systems end to end, who can lead, mentor, and grow ML/Natural Language Processing (NLP) engineers along with the team manager. You partner with cross-functional stakeholders to design a high-value roadmap that scales the impact of ML for customers, and you make prioritization and architecture decisions to drive the execution of this roadmap. Given you are constructing the foundation on which our global data infrastructure will be built, you need to pay close attention to detail and maintain a forward-thinking outlook as well as scrappiness for the present needs. You lead by example to build a cohesive team culture of ownership, growth, transparency, and customer focus, and you attract and close top talent for your team




Responsibilities









  • Mentoring: coach and grow ML/NLP engineers by guiding their professional development in conjunction with the team manager and taking a hands-on approach to day-to-day collaborative problem solving


  • Strategy: actively participate in customer engagements and partner with cross-functional stakeholders (legal product managers, customer success) to discover new opportunities to apply ML/NLP to solve critical problems and design a high-value roadmap that scales the impact of ML for customers


  • Execution: make customer-centric prioritization decisions to balance between immediate impact and long-term bets with limited resources and partner with the team manager to drive alignment and collaboration with other engineering teams


  • Design: deeply understand how everything fits together; architect systems to balance scrappiness for the current needs with a forward-thinking outlook to improve and scale our infrastructure; continuously look for opportunities to automate and build tools to lower operational barriers


  • Hands-on problem solving: help the team solve its most complex problems with the simple, pragmatic solutions


  • Culture: lead by example to build a cohesive team culture of ownership, growth, transparency, and customer focus


  • Hiring: attract and close top ML/NLP engineers and software engineers for your team




You are a good fit if you:





  • Have an exceptional track record of successfully delivering large scale ML/NLP models and systems that result in substantial positive impact to customers across multiple organizations (7+ years)


  • Have a track record of building teams that consistently deliver results and investing in the learning and growth of the people you lead


  • Are a creative and strategic thinker with a change agent mindset who enjoys identifying business problems with the highest impact for customers and designing end-to-end ML/NLP models and systems to address them


  • Have a “get stuff done” attitude and enjoy being hands-on and working alongside the team to solve its most pressing problems in a fast-paced, collaborative environment


  • Are a skilled technical influencer with a track record of successfully influencing product direction through a strong perspective that motivates engineers to develop simple, pragmatic solutions to complex problems


  • Are an expert communicator with clear and concise, active listening and empathy skills, and a respectful, collaborative approach that earns the trust of your peers


  • Are a strong source of ML/NLP engineering and software engineering talent and are comfortable closing applicants for your team

Source

https://www.indeed.com/jobs

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