Machine Learning EngineerRebel Space Technologies, Inc. • United States
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Machine Learning Engineer
Rebel Space Technologies, Inc.
- United States
- United States
À propos
Define and own system-wide data architecture that integrates data components across the Rebel Space autonomy stack for enhanced analysis and insights.
Research, prototype, and survey different ML architecture and workflow optimization techniques
Develop proofs-of-concept of customized optimizations that demonstrate the benefit of your optimizations on real-world models using real-world datasets.
Develop data collections, labeling pipelines, and evaluation pipelines. Research and develop machine learning models for physical sensor systems.
Extend existing ML libraries and frameworks.
Create and deliver reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews.
Own technical projects from start to finish and be responsible for major technical decisions and tradeoffs. Effectively participate in team planning, code reviews, and design discussions.
Basic Qualifications:
Bachelor's degree in Computer Science, Electrical Engineer, Physics or related technical discipline.
3+ years of relevant industry experience in data analytics and machine learning
Strong expertise in scientific Python (NumPy, SciPy, Pandas) and modern ML frameworks (PyTorch, TensorFlow, JAX, Scikit-Learn, Keras)
Proficiency in SQL and experience with relational or time-series databases
Proven experience applying statistical modeling, data analysis, and inference to extract actionable insights from large and complex datasets
Familiarity with overall big data analysis, system backend integration with new ML systems, and large-scale data processing
Proficiency in data visualization tools (e.g., Matplotlib, Seaborn, Power BI) to effectively communicate findings
Excellent understanding of algorithms, data structures, and coding standards
Strong communication and behavioral skills
Motivated self-starter that can work autonomously and as part of a team
Preferred Qualifications:
PhD, Masters, or equivalent in Computer Science, Electrical Engineer, Physics or related field with 5+ years of professional experience in machine learning engineering
Knowledge of experiment tracking, model deployment strategies, data versioning, and monitoring
Experience with ML infrastructure tools (e.g. MLflow, Kubeflow, Airflow, feature stores, model registries)
Prior experience with real-time data processing, prediction systems, or active learning pipelines
Experience designing reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews
Experience at early-stage startups and remote-first organizations
Passionate about building autonomous systems
Benefits:
Premium Healthcare Benefits: We offer comprehensive medical, dental, and vision plans at little to no cost to you.
Stock Options: Own meaningful equity in Rebel Space.
Generous PTO: Includes flexible vacation and company paid holidays.
Maternity/paternity leave.
Flexible hybrid work options.
Opportunity to shape the future of space cybersecurity and observability!
The estimated salary range for this role is $140,000-$200,000 + equity in the company, inclusive of all levels/seniority within this discipline. As a growing company, the salary range is intentionally wide as we determine the most appropriate package for each individual taking into consideration years of experience, location, educational background, and unique skills and abilities as demonstrated throughout the interview process. ITAR Requirements: To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), applicants must be a US citizen, lawful permanent resident of the U.S., protected individual as defined by 8 USC 1324b(a)(3), or eligible to obtain the required authorization from the US Department of State. Learn more about the ITAR here. Rebel Space Technologies is an equal-opportunity employer, and we encourage candidates from all backgrounds to apply. If you are someone passionate to work on problems that matter, we’d love to hear from you.
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Compétences linguistiques
- English
Avis aux utilisateurs
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