Principal Machine Learning Engineer
1 month ago
Job Description
About the Company: Our company is at the forefront of space exploration and technology, dedicated to unlocking the mysteries of the universe and making space more accessible. We are pioneering new technologies in spacecraft design, propulsion, and remote sensing, with a focus on sustainable exploration and the utilization of space resources. Join us to be part of a visionary team of space enthusiasts and technologists who are shaping the future of interplanetary travel and exploration, where your work contributes to groundbreaking missions and the expansion of human presence in space.
Responsibilities:
- Lead the development of machine learning models to analyze and interpret vast amounts of data from space missions, enhancing our understanding of the cosmos and improving mission efficiency.
- Design and implement AI-driven systems for autonomous spacecraft navigation, anomaly detection, and real-time decision-making in complex space environments.
- Collaborate with astronomers, engineers, and data scientists to integrate AI into our space exploration programs, ensuring the seamless operation of spacecraft and rovers.
- Develop predictive models for space weather and celestial phenomena, aiding in mission planning and risk assessment.
- Innovate in the field of remote sensing, applying machine learning to process and analyze satellite imagery for Earth observation, planetary science, and resource mapping.
- Spearhead research initiatives to leverage AI in the development of life support systems, habitat automation, and sustainable space living solutions.
- Establish scalable data pipelines and infrastructure to support AI/ML operations in space and ground-based systems.
- Promote a culture of continuous learning and experimentation, staying abreast of advancements in AI, machine learning, and space technology.
- Engage in cross-sector collaborations to drive innovation in space technology, participating in conferences, workshops, and industry consortia.
- Mentor and lead a team of machine learning engineers and data scientists, guiding project direction and fostering professional growth.
Requirements
Minimum Requirements:
- Passionate about space exploration and a strong desire to contribute to pioneering space missions.
- 6+ years of experience in machine learning and AI, with specific expertise in areas relevant to space technology, such as robotics, remote sensing, or autonomous systems.
- Advanced understanding of ML algorithms, data processing, and statistical methods, with the ability to apply these in high-stakes, technically complex environments.
- Proficiency in programming languages such as Python and C++, and familiarity with ML frameworks like TensorFlow, PyTorch, and Huggingface.
- Excellent analytical, problem-solving, and communication skills, with experience in interdisciplinary collaboration.
- A Master’s or PhD in Computer Science, Aerospace Engineering, Astrophysics, or a related field.
Preferred Requirements:
- Direct experience in the space industry or working on space-related technology projects.
- Published research or demonstrated innovation in the application of AI/ML to space exploration, robotics, or Earth observation.
- Knowledge of satellite communication systems and data transmission in space environments.
- Experience with simulating space missions or developing AI systems for space operations.
Benefits
- Competitive salary range ($210k - $290k) with equity options in a pioneering space exploration company.
- Unique opportunities to contribute to high-profile space missions and technologies.
- Flexible work arrangements, including remote work options and a focus on work-life balance.
- Comprehensive health, dental, and vision insurance, with additional support for mental and physical wellness.
- Continuous learning and development opportunities, including access to seminars, workshops, and training in space technology and AI.
- A collaborative and innovative work environment, where creativity and groundbreaking ideas are actively encouraged and supported.
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