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Senior Mission Operations Engineer
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Added 10 mins ago
Senior RF/Microwave Design Engineer
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Senior Machine Learning Engineer
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Treasure AI

Senior Machine Learning Engineer

Remote, United States

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Job details

Experience: ● 6+ years of professional experience in software engineering designing and building ML-
Posting language: English
Posted: Sep 14, 2026

Original job description

Treasure AI:

At Treasure AI, we’re on a mission to radically simplify how companies use data to create connected customer experiences. Our sophisticated cloud-based customer data platform drives operational efficiency across the enterprise to deliver powerful business outcomes in a way that’s safe, flexible, and secure. We are thrilled that Gartner Magic Quadrant has recognized Treasure AI as a Leader in Customer Data Platforms for 2024! It's an honor to be acknowledged for our efforts in advancing the CDP industry with cutting-edge AI and real-time capabilities. View the report here. Furthermore, Treasure AI employees are enthusiastic, data-driven, and customer-obsessed. We are a team of drivers - self-starters who take initiative, anticipate needs, and proactively jump in to solve problems. Our actions reflect our values of honesty, reliability, openness, and humility.

Your Role:

We are seeking strong ML engineers to join the ML team and help us sharpen the ML vision and deliver more solutions to satisfy our customers’ needs. You will be working closely with other ML engineers and people from cross-functional teams.

You will be a good fit if you:

Are a self-driven, organized, and independent individual who proactively takes initiatives, anticipates needs, and solves problems to contribute to delivering values to our customers.
Have a strong sense of ownership and responsibility to get things done.
Have a growth mindset; are curious to learn new things and adaptive to changes.
Know how to navigate ambiguity and thrive in uncertain environments, consistently driving work forward.
Are passionate about productizing ML products, knowing how to make practical trade-offs when turning ideas into working software.
Excel in adapting communication styles and simplifying complex technical concepts for diverse audiences, ensuring clear and effective communication.
Enjoy working in a collaborative work environment with people from diverse backgrounds.

This is an ideal position for those with not only data science and machine learning skills, but also cloud service engineering skills for developing, deploying, and operating these critical ML products.

Responsibilities:

Design and develop ML models or solutions for our client CDP implementation.

Own specific technical areas, drive and execute ML product projects, track progress and mitigate risks by collaborating closely with product managers, UX designers, architects, engineers, and stakeholders from other cross-functional teams.
Contribute to defining system architecture for the ML products and implementing specific components to enhance the user experience.
Design and implement performant, scalable ELT data pipelines, considering an ML model’s lifecycle (training and inference).
Take responsibility for technical problem solving and meeting ML objectives creatively in ambiguous scenarios.
Participate in the on-call rotation for production support.
Drive best practices including ML research methodologies, coding standards, code reviews, source control management, development processes, build processes, testing and release, and operational excellence.

Job Requirements:

Advanced degree in computer science, data science, machine learning, or related field, or equivalent work experience.

6+ years of professional experience in software engineering designing and building ML- driven products, with at least 3 years focused on production ML systems.
Fundamental knowledge of Data Engineering and extensive experience in developing and deploying ML models, as well as building and maintaining ML pipelines and products.
Experience in applying scientific method: hypothesis formulation and testing, exploratory data analysis, cross-validation, reproducible research, structured reporting/documentation in a structured format, result explanation and presentation.
Experience designing, deploying, and operating scalable ML systems in production. This includes responsibility for model selection, performance benchmarking, and lifecycle management to solve real-world business problems.
Proficiency in Python and general ML ecosystem tooling in data processing and modelling (such as NumPy, pandas, scikit-learn, PyTorch, etc.).
Experience in designing and building products using public cloud services such as AWS.
Excellent verbal and written communication skills in English, and ability to convey research findings and implications to both technical and non-technical audiences.
Ability to work effectively in cross-functional and distributed teams across different time zones.

Physical Requirements:

Remote Work

Travel Requirements:

Our Dedication to You:

We value and promote diversity, equity, inclusion, and belonging in all aspects of our business and at all levels. Success comes from acknowledging, welcoming, and incorporating diverse perspectives.

Diverse representation alone is not the desired outcome. We also strive to create an inclusive culture that encourages growth, ownership of your role, and achieving innovation in new and unique ways. Your voice will be heard, and we will help amplify it.

Agencies and Recruiters:

We cannot consider your candidate(s) without a contract in place. Any resumes received without having an active agreement will be considered gratis referrals to us. Thank you for your understanding and cooperation!

This description captures the core of the role today. As we adopt AI and new ways of working, responsibilities may evolve, and we encourage team members to take initiative, lean into change, and help expand the impact of their role beyond what’s listed here.

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More about this job

Skills

Machine learning
ML
Communication skills
Data engineering
Problem solving
Research
Computer science
Data analysis
Reporting
Documentation
Python
Process data
NumPy
pandas
Scikit-learn
PyTorch
AWS

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