Staff Software Engineer (IR Data Products)

• This role is an architecture and technical-leadership seat for the Software focus area of the IR Data Products team
• The engineer will own architecture and cross-team execution across defined IR data-system domains, translating longer-term technical direction into multi-quarter designs and delivered production systems
• This role will lead multi-quarter initiatives to design and build scalable software architectures that make the system fast, cheap, reliable, evolvable, and ready for many-satellite scale
• In this role, the candidate will work across four key areas:
• Architecture & implementation leadership for the next-year horizon: Own key aspects of the architectural direction for the data systems for Muon’s IR Missions — pre-processing, processing directives & routing, delivery orchestration, compliance evaluation, and the orchestration platform itself
• Low-latency optimization & core infrastructure: Own key aspects of the technical roadmap to low-latency processing. Own structural designs such as event-driven microservices, cloud infrastructure design and optimization, and algorithmic optimizations
• Geospatial tooling: Own key aspects of the architectural direction for how we store, catalog, serve, and version geospatial data (NetCDF, Zarr, HDF, STAC, tile stores) at scale
• MLOps foundations: Build the production foundations for ML products — model packaging, experiment tracking, GPU-backed training and inference — that our derived-product work (hotspots, perimeters, fire behavior) will increasingly depend on
• Additionally, the role will represent the team in cross-functional design reviews, drive prioritization syncs with Technical Program Managers and Business Development, and set software standards for the team’s codebase and development practices
• This engineer will mentor senior and mid-level engineers across the team and raise the bar on how we reason about failure modes, immutability, idempotency, and reprocessing
• Own key aspects of the architectural design for the multi-mission, multi-customer IR data systems in partnership with the Principal Software Engineer: ingest, pre-processing, orchestration, storage and catalog, delivery, and the platforms that run all of the above
• Lead the design and implementation of critical capabilities for Muon’s IR missions from problem framing and design document through rollout, adoption, and operational hand-off
• Own key aspects of the technical roadmap to low-latency processing including: structural designs such as event-driven microservices, cloud infrastructure design and optimization, and algorithmic optimizations
• Set direction for geospatial data storage, cataloging, and serving at scale — including tradeoffs across formats, tile stores, STAC catalogs, bucket and IAM topology, and reprocessing / versioning strategy
• Design and build the MLOps foundations for derived IR products — model packaging and versioning, experiment tracking, GPU-backed training and inference, A/B evaluation harnesses, and reproducibility — so ML-driven products can move from research to production on a well-paved path
• Set software standards for the team — codebase organization, release engineering, CI, testing, documentation, code review, observability, and operational excellence — and raise the bar on how the team reasons about failure modes, immutability, idempotency, and reprocessing
• Provide technical leadership across functions: coordinate design and implementation with Product, Program Management, Business Development, and other Software teams; represent IR Data Products in cross-functional design reviews and design processes; and turn ambiguous requirements (latency budgets, compliance constraints, new missions, new customers) into concrete engineering plans

Benefits

• 100% health, dental, and vision coverage for employees; 50% coverage for dependents (Concierge Medical offered through One Medical where available)
• Parental leave for primary and secondary caregivers
• Generous time off policy
• 401(k) plan through Betterment and equity management through Carta
• Fully stocked kitchen at our HQ and we cater lunch 3 days per week
• Dog-friendly office- The ideal candidate is a hands-on staff-level engineer with a track record of leading multi-quarter architectural initiatives on production data platforms at scale
• They combine deep experience with distributed data systems and modern workflow orchestration with real geospatial and (ideally) MLOps depth, and they are as comfortable writing a design document and driving cross-team alignment as they are debugging a complex piece of algorithm code
• Experience with latency optimization: measurement discipline, benchmarking, per-stage instrumentation, right-sizing, fan-out, caching, async I/O, and knowing when the answer is structural rather than algorithmic
• Strong operational mindset: observability, SLOs, on-call, safe deploys, hotfix protocols, immutability, and reproducibility
• Demonstrated experience designing and operating production data pipelines on AWS with a modern workflow orchestrator (e.g., Flyte, Airflow, Prefect, Argo, or equivalent)
• Excellent technical writing and cross-functional communication — comfortable driving alignment across engineers, scientists, PMs, and adjacent platform / flight-software teams
• Bachelor’s degree with 10+ years or MS with 8+ years or PhD with 5+ years of software engineering experience
• Demonstrated success as a technical leader on production data platforms at scale — with the designs and rollouts to show for it
• Track record of leading multi-quarter architectural initiatives that spanned multiple services or teams
• We encourage you to apply, even if you don’t check all the boxes, and we look forward to reviewing your application!
• Applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157
• Experience with event-driven / microservices architectures: queues, event routing, backpressure, idempotency, retries, DLQs, and clear service contracts
• Terraform / IaC ownership of AWS resources, and hands-on experience shaping IAM boundaries between environments
• Familiarity with modern workflow platforms such as Union.ai / Flyte v2
• Prior work on geospatial / remote sensing systems at scale
• Fluent with the tradeoffs behind geospatial storage formats, tile stores, and STAC
• Hands-on MLOps experience: model packaging and versioning, experiment tracking (MLflow, W&B, or similar), GPU-backed training and inference, feature stores, A/B harnesses
• Experience with GPU acceleration for image processing (e.g., JAX, CuPy, CUDA) or ML inference at scale
• Experience in satellite ground-segment or a comparable domain where compliance, provenance, and data lineage are first-class concerns
• Experience introducing latency SLOs and benchmarking discipline to a team
• Prior experience serving imagery / tiled geospatial data to external customers or partner platforms