Machine Learning Engineer II, NavSDK
Mapbox
This job is no longer accepting applications
See open jobs at Mapbox.See open jobs similar to "Machine Learning Engineer II, NavSDK" Foundry.Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 3.5 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.
What We Do
Our team is revolutionizing in-car experiences with MapGPT, an advanced in-car assistant powered by location intelligence. Our product enables natural and in-depth conversations about directions, landmarks, roads, and other highly dynamic aspects of the world, constantly updated with Mapbox location data. Our team is at the forefront of developing and implementing the cutting-edge models that power MapGPT's conversational abilities.
We use models to integrate sophisticated natural language understanding into real-world applications for both cloud and on-device use. Our work spans across multiple domains, including natural language processing, speech recognition, and machine learning-based recommendations, all tailored for the unique challenges of an in-car environment.
What You'll Do
Evaluate and implement models for both cloud-based and on-device applications, ensuring optimal performance, latency, and privacy for MapGPT’s natural language understanding.
Integrate these models into MapGPT, enhancing its ability to engage in actionable natural conversations.
Develop and optimize ML-based recommendation systems to improve our ability to suggest relevant points of interest, routes, and location-based services.
Help design, develop, and manage our MLOps pipeline for training, evaluating, and deploying models for different use cases, languages, and deployment targets.
Contribute to the improvement of Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems, ensuring high-quality voice interactions in various acoustic environments typical of in-car use.
Collaborate with other teams to ensure that our machine learning features align with user needs, automotive industry standards, and Mapbox’s broader location intelligence ecosystem.
Stay at the forefront of NLP and ML research, continuously evaluating and implementing new techniques to enhance our team's capabilities and product user experience.
What We Believe are Important Traits for This Role
5+ years of relative industry engineering experience.
3+ years of professional experience in machine learning, with a focus on NLP and transformer models.
Technical Proficiency: Strong programming skills in Python, experience with ML frameworks such as PyTorch or TensorFlow, and experience with MLOps and deploying ML models in production environments hosted on AWS.
Strong Product Focus: Ability to translate ML capabilities into tangible product features, understanding that your work directly impacts the end-user experience of MapGPT.
Practical Problem-Solving: Skill in balancing theoretical knowledge with practical implementation, focusing on solutions that work effectively in real-world, in-car environments.
Collaborative Mindset: Willingness to work closely with product, engineering, and design teams to create integrated solutions that meet user needs and business goals.
Adaptability and Learning Agility: Enthusiasm for staying current with rapidly evolving ML technologies and ability to quickly apply new learnings to improve MapGPT.
Iterative Approach: Comfort with rapid prototyping, testing, and refining models based on real-world feedback and usage data.
Nice to Have Traits for This Role
Experience with speech recognition (ASR) and text-to-speech (TTS) systems
Experience with low-latency ML model development and use
What We Value
In addition to our core values, which are not unique to this position and are necessary for Mapbox leaders:
We value high-performing creative individuals who dig into problems and opportunities.
We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people.
We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.
We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.
Our annual base compensation for this role ranges from $159,375 - $215,625 for most US locations and 5% to 10% higher for US locations with a higher cost of labor. Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Please discuss your specific work location with your recruiter for more information.
By applying for this position, you acknowledge that you agree to the Mapbox Privacy Policy which is linked here.
Mapbox is an EEO Employer - Minority/Female/Veteran/Disabled/Sexual Orientation/Gender Identity.
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This job is no longer accepting applications
See open jobs at Mapbox.See open jobs similar to "Machine Learning Engineer II, NavSDK" Foundry.