Senior Machine Learning Engineer

About Us

We reimagine how satellites process and deliver intelligence from orbit. Our satellite edge computing solutions enable real-time analysis, rapid decision-making, and reduced data downlink needs.

Our vision is to turn satellites into autonomous, intelligent systems that interpret data instantly. This unlocks critical advantages in defense, environmental monitoring, and global communications, providing insights with speed, efficiency, and security from space.

As a part of our team, you'll work on the space data analytics product Orbitfy, exploring use cases for the technology and collaborating with the CTO to strategize the product and company roadmap.

LPL's data science team is at the heart of our product development, offering space-derived analytics as the source of truth for key stakeholders.

We're looking for someone who leverages AI tools to boost productivity and accelerate results. You'll work closely with engineering, product, and the CTO to apply sophisticated modeling techniques to a modern data stack and build the future of Space Edge Computing.

This remote-first role requires excellent communication skills to coordinate with global teams and external partners.

Main Responsibilities:

1. Ai-Driven Development: Use modern AI tools to enhance productivity across the data science lifecycle (data wrangling, model design, testing, documentation, etc.).
2. Algorithm Development: Design and implement state-of-the-art computer vision and ML models for satellite imagery (optical, SAR, multispectral, hyperspectral, thermal).
3. Model Optimization: Train and fine-tune deep learning models for edge deployment (on-board satellites), balancing performance with efficiency, power, and computational constraints.
4. MLOps and Orchestration: Provide best practices for MLOps, orchestration, and workflow.
5. Cross-Functional Collaboration: Work with GIS engineers, software teams, and product managers to integrate ML solutions into Orbitfy's pipeline.
6. Innovation & Research: Stay ahead of emerging trends in Edge AI, ML, and remote sensing, translating them into practical solutions for space applications.
7. Data Handling: Process large, complex datasets from diverse sensors; design robust preprocessing, augmentation, and feature extraction workflows.
8. Communication & Reporting: Clearly articulate technical concepts, results, and trade-offs to both technical and non-technical stakeholders.
9. Quality & Validation: Ensure robustness, reliability, and reproducibility of solutions through systematic testing, benchmarking, and validation.
10. Documentation and Reporting: Maintain detailed documentation of algorithms, models, and processes; prepare reports and presentations for technical and non-technical audiences.

Success Metrics:

1. Delivery of machine learning modules on schedule for satellite missions or user trials.
2. Work on the deployment of products for multiple satellite missions.
3. Demonstrated productivity gains and accelerated project outcomes through the adoption of AI tools.
4. Effective collaboration and communication across distributed teams.
5. Contributions shaping the product roadmap and strengthening our position in edge-based space intelligence.

Requirements:

1. Education: Bachelor's or Master's in Computer Science, Data Science, Artificial Intelligence, or a related field.
2. Experience: 3–8 years in data science, with demonstrated hands-on experience in computer vision, image processing, or machine learning.
3. Technical Skills:

•  > Strong in Python; experience with frameworks like TensorFlow, PyTorch, OpenCV.

 > General Software engineering: cloud infrastructure, Docker, git best practices, etc.

 > Exposure to C/C++, CUDA, ONNX, TensorRT, OpenVINO, or FPGA acceleration is a plus.

 > Experience with architectures such as CNNs, ViTs, GANs and foundational models etc.

 > Experience with model compression is a plus..

Domain Knowledge:

•  > Familiarity with satellite imagery and remote sensing preferred (but not mandatory if strong ML background).
• Good understanding of embedded systems from the perspective of deploying AI.
• Edge AI Focus: Experience or keen interest in deploying models in constrained environments (e.g., embedded systems, on-board devices).
• Experience or understanding of FPGAs is desirable, not mandatory.
• Experience working with NVIDIA Jetson and Xilinx Versal will be a big plus. Candidates with such experience will be preferred.
• Soft Skills:

•  > Ability to work independently in a remote-first setup.

 > Excellent communication skills to bridge technical and product conversations across geographies.

 > Curiosity, creativity, and a problem-solving mindset.

Equal Opportunity Employment Information:

Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.