Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
Loading job details
Senior Data Scientist
- Type
- Full time
- Posted
- 3M AGO
About the role
Job Purpose/Summary
The Senior Data Scientist is the technical lead and line manager for the data science and data engineering team supporting Knowmadics' Embedded Systems and Electronic Warfare product portfolio. The role oversees three to five Data Scientists and Data Engineers who are commonly embedded in or tasked to specific products and customer-funded programs. Product and program leaders own the outcomes and priorities of those efforts; this role owns the people, the technical quality of the team's work, and the sustainable allocation of the team across the portfolio.
Reporting to the CPTO, this is a hands-on player-coach role at the career level (L5). The Senior Data Scientist is the technical reference for the portfolio's data and machine learning work: signal and sensor data pipelines, feature and model development, evaluation, and the delivery of trained models onto embedded, size-, weight-, and power-constrained hardware. The role contributes directly to data strategy, technical spikes, prototypes, evaluation plans, and early implementation, and works with embedded, firmware, RF, platform, and DevSecOps engineers early enough that data contracts, inference budgets, and deployment pathways are settled before hardware and software choices harden.
The technical domain is machine learning over radio-frequency and electromagnetic spectrum data and other high-rate sensor streams: signal detection, classification, and characterization; emitter and behavior analysis; anomaly detection over time series; sensor fusion; and real-time inference on edge processors, GPUs, SoCs, and FPGAs in disconnected, intermittent, and low-bandwidth environments. The role drives technical direction within this domain and contributes to Knowmadics' shared data science practice, standards, and reusable components across the wider AI/ML community.
Success in this role looks like a small team that receives consistent coaching while embedded across products, data pipelines and labeled datasets that are trusted and reusable, models whose evaluated performance holds up on the target hardware and under operational stress, and technical decisions made early enough that they survive the transition from prototype to fielded product.
Duties and Responsibilities
People and Team Leadership
• Serve as the formal line manager for three to five Data Scientists and Data Engineers; own one-on-ones, coaching, performance reviews, goal setting, development planning, and hiring recommendations for the team.
• Allocate team members across the portfolio's product and program teams, clarify priorities and expected outcomes, manage workload and context switching, and remain accountable for employees embedded in matrixed teams.
• Mentor and sponsor team members through model and code reviews, pairing, and shared patterns; identify capability gaps in the team and close them through hiring, training, or reassignment.
Technical Leadership and Delivery
• Act as the technical reference for data science and data engineering across the portfolio; own the quality bar for data pipelines, features, models, evaluation, and model packaging for embedded targets, and ensure it is met.
• Contribute directly during early program formation through data strategy, technical spikes, prototypes, and risk-reduction experiments in partnership with embedded, firmware, RF, platform, and DevSecOps engineers.
• Translate mission workflows and sensor characteristics into data collection and labeling plans, model choices, evaluation criteria, data contracts, and inference budgets; make explicit build, buy, partner, and reuse recommendations within the domain.
• Design and oversee data engineering for high-rate signal and sensor data: capture, storage, labeling, versioning, synthetic and augmented data, and the pipelines that feed training and evaluation.
• Deliver models that run within the compute, memory, power, latency, and connectivity limits of the target hardware, using model compression, quantization, hardware-aware architectures, and hardware-in-the-loop testing.
• Apply the company's standards for reproducibility, MLOps, model evaluation, Responsible AI, security, traceability, human oversight, monitoring, and rollback, and contribute improvements to them from the portfolio's experience.
• Lead model and data reviews and root-cause analysis within the portfolio; identify data, performance, integration, sustainment, and security risks early and raise cross-cutting risks to the CPTO and product leads.
Customer and Business Support
• Serve as a trusted technical advisor to the portfolio's customers and partners on what the data and models can and cannot do, including capability limits, uncertainty, and operational tradeoffs.
• Support proposal capture, customer discovery, estimates, program reviews, test events, and demonstrations; identify follow-on opportunities from patterns across programs and customer needs.
Qualifications
Required
• 6+ years of progressive experience building and deploying machine learning or signal-processing systems, including at least 2 years leading the technical work of others through mentorship, technical lead, or line management roles.
• The stated experience and education requirements describe the typical path to this level and are not a gate. Knowmadics will consider an equivalent combination of education, professional experience, and demonstrated skill, and makes exceptions for candidates who can evidence the scope, complexity, and judgment the role requires.
• REQUIRED: Eligible to obtain a U.S. Security Clearance - U.S. Citizenship required. An active DoD Secret or higher clearance is preferred; ability to obtain TS/SCI is strongly preferred.
• Bachelor's degree in Data Science, Computer Science, Electrical or Computer Engineering, Applied Mathematics, Physics, or a related STEM field; advanced degree preferred.
• Demonstrated end-to-end ownership of production machine learning systems, from raw sensor data through evaluation to deployed inference, and experience coaching technical employees across product or program teams.
• Strong hands-on capability in Python and frameworks such as PyTorch or TensorFlow, with practical experience in digital signal processing, time-series and spectral feature engineering, experiment tracking, model registries, and data versioning.
• Experience deploying models to embedded or edge targets, including model compression and quantization, inference runtimes such as ONNX Runtime, TensorRT, or TensorFlow Lite, and validation against the target hardware.
• Working knowledge of data engineering fundamentals: streaming and batch pipelines, storage formats for large signal datasets, labeling workflows, data quality checks, and reproducible dataset builds.
• Experience designing for latency-sensitive, resource-constrained, disconnected, or otherwise operationally demanding environments, with disciplined evaluation, traceability, and rollback.
• Excellent written and verbal communication skills, including technical documentation and briefings for engineering, executive, operator, and customer audiences.
Strongly Preferred
• Experience applying machine learning to RF signal detection and classification, modulation recognition, emitter characterization, direction finding, spectrum sensing, or electronic support and electronic warfare problems.
• Experience with software-defined radio, IQ data capture, FPGA or SoC-based signal processing, and hardware-in-the-loop or over-the-air testing.
• Experience with DoD open-architecture and interoperability expectations, tactical edge hardware, government programs, or startup and scale-up product environments.
• Prior line management of a small technical team.
• Active DoD Secret, Top Secret, or TS/SCI clearance.
Working conditions
• REQUIRED: Employees may be called upon to participate in in-person meetings, trainings, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position.
• Remote, with preference given to candidates located within approximately 40 miles of Wichita, KS; Lawton, OK; or Round Rock, TX. Relocation assistance may be negotiable for the right candidate.
• Estimated travel: 10-25 percent to customer sites, government program reviews, partner facilities, test events, demonstrations and exercises, industry events, and Knowmadics offices.
• Some weekend or off-hours work may be required to support test windows, customer demonstrations, deployment cutovers, incident investigation, or operational deadlines.
• Standard business hours with flexibility to support distributed teams and customers across U.S. time zones.
Physical requirements
May include sitting or standing for extended periods, working with computers and technical equipment, occasional lifting or moving of materials and equipment up to 35 lbs, and travel to field, range, or demonstration environments where conditions may include outdoor weather, noise, and the operational tempo typical of defense exercises.
Direct reports
Three to five Data Scientists and Data Engineers. Team members may be embedded in or tasked to specific products and programs, but this role remains their formal line manager and is accountable for performance, growth, workload, technical development, and sustainable allocation.
