Senior Machine Learning Engineer, Caper

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer, Caper in United States.

This role offers the opportunity to drive cutting-edge machine learning solutions in a fast-paced, sensor-driven environment. You will work closely with engineers across computer vision, hardware, and frontend domains to design, implement, and deploy models that enhance real-world user experiences. The position focuses on integrating and fusing multimodal sensor data to enable intelligent, scalable, and seamless product interactions. You will take ownership of end-to-end ML workflows, from research and model development to production deployment on edge devices. This role encourages innovation, collaboration, and hands-on implementation of complex machine learning systems. You will influence both system architecture and product strategy, making a tangible impact on customer-facing technology.

• Accountabilities:
• Design, implement, and deploy machine learning models that leverage multi-sensor data to improve product interactions.
• Drive end-to-end ML solutions, including model research, training, evaluation, and deployment.
• Build and maintain infrastructure for collecting, processing, and storing sensor data efficiently.
• Deploy models at the edge using platforms such as Nvidia Jetson.
• Collaborate with cross-functional teams to inform system design and contribute to product vision.
• Continuously improve ML workflows, architectures, and data pipelines to ensure scalability and performance.
• Mentor team members and share best practices in model development and deployment.
• Requirements:
• Master’s or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or related fields.
• 3+ years of experience in sensor fusion, multi-modal learning, transformers, video understanding, or activity recognition.
• Strong programming skills in Python, C++, Java/Kotlin.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Familiarity with data science tools such as SQL, Pandas, and similar technologies.
• Proven track record of delivering end-to-end ML solutions from research to production.
• Strong communication, collaboration, and presentation skills to work with diverse stakeholders.
• Preferred: experience with large language models (LLMs), vision-language models (VLMs), edge computing, onboard hardware deployment, A/B testing, and translating research into production.
• Benefits:
• Competitive salary based on location, with equity grants and potential for annual refresh grants.
• Fully remote, flexible work arrangements with a “Flex First” approach.
• Opportunities to lead high-impact ML projects with cutting-edge sensor and AI technology.
• Professional growth through collaboration with a cross-functional, global team.
• Comprehensive benefits package including medical, dental, vision, and retirement plans.
• A culture of innovation, inclusion, and mission-driven impact.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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