ABOUT THE TEAM

At Anduril, our Software Engineers specialize in solving complex, real-world problems through cutting-edge algorithms and intelligent software integrations. Operating in small, innovative teams, we push the boundaries of what's possible to deliver advanced technologies with mission-critical applications. Our commitment doesn't end with academic research or proof-of-concept experiments; we measure our success by the real-world impact of our deployed solutions. Inspired by Arthur C. Clarke’s vision — “Any sufficiently advanced technology is indistinguishable from magic” — we aim to achieve groundbreaking results in target tracking, state estimation, and situational awareness. We are currently seeking highly talented technologists to join our mission and redefine the future of defense technology.

WHAT YOU WILL DO:

• Define and influence the direction of a small team, leveraging your subject-matter expertise in target tracking and state estimation.
• Prototype and deploy state-of-the-art algorithms for tracking, multi-sensor data fusion, and state estimation in agile, iterative development environments.
• Develop high-performance software for real-time systems, ranging from tactical implementations to simulation environments and decision support tools.
• Design and implement robust filters, estimators, and probabilistic reasoning systems that enable actionable insights from noisy, ambiguous, or incomplete sensor data.
• Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate the benefits of our technology.
• Drive customer success by customizing algorithms and software for mission-critical use cases, including real-time tracking and sensor fusion.
• Integrate tracking and estimation technologies into the broader software development lifecycle, from requirements definition through testing and optimization.
• Translate technical progress into clear, actionable insights for diverse stakeholders, including colleagues and end-users.

REQUIRED QUALIFICATIONS

• Proficiency in algorithm design, software development, and statistical modeling with programming expertise in C/C++, Python, and Matlab.
• Strong knowledge of target tracking techniques, such as Kalman filters, particle filters, and multi-target tracking algorithms (e.g., JPDA, MHT, or PHD filters).
• Experience in state estimation, including Bayesian filtering, sensor fusion, and recursive estimation techniques.
• Solid understanding of applied mathematics, including linear algebra, optimization, probability, and stochastic processes.
• Knowledge of signal processing techniques for interpreting diverse sensor data (e.g., radar, lidar, EO/IR).
• Familiarity with big data pipelines, NoSQL databases, and the efficient handling of large-scale sensor data.
• Background in machine learning as applied to target tracking and recognition, including clustering, classification, and anomaly detection techniques.
• Ability to engineer robust systems for estimation theory, adaptive filtering, controls, and complex signal environments.
• Demonstrated ability to work across development lifecycles, from prototyping to optimizing production systems.
• Eligible to obtain and maintain an active U.S. Top Secret security clearance.

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

ABOUT THE TEAM

Anduril's Software Engineers excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our software engineers build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Anduril is seeking talented “magicians” to join in our mission to expand the boundary of what’s possible. 

WHAT YOU WILL DO:

• Contribute to the direction of a small team with your expertise and ideas
• Prototype state-of-the-art software solutions in an agile development environment
• Implement high-performance software spanning the spectrum from tactical systems to web applications
• Use high-fidelity modeling and simulation environments, innovative analysis tools, and sound analysis techniques to quantify the benefit of our technology
• Engage with our customers, to ensure successful outcomes for their mission-critical needs
• Work with all aspects of the software development lifecycle
• Help your colleagues and customers understand what you’re doing and why

REQUIRED QUALIFICATIONS

• 8+ years of professional software engineering experience
• Bachelor's degree in mathematics, physics, engineering, or other technical field (advanced degree strongly preferred)
• C/C++, Python, and Matlab;
• Big data/NoSQL/database technologies;
• Software engineering: software design, algorithm implementation, and software analysis, testing, and optimization;
• Machine learning: supervised and unsupervised learning, clustering, and classification;
• Applied mathematics: differential equations, linear algebra, optimization, statistics, and random processes;
• Engineering: controls, estimation theory, and digital signal processing.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

Position Summary: 

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineer.  We are looking for a software engineer with machine learning expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services. 

In this role you will be expected to design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. The ideal candidate should be passionate about applying AI/ML concepts to difficult problems and develop scalable solutions. We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare. 

Responsibilities: 

• Develop and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. 

• Develop and maintain backend services using Python, focusing on AI-driven applications. 

• Design and implement APIs for seamless integration with AI models and services. 

• Develop tools for large-scale data processing and ETL and contribute to extracting insights from data to help guide ML systems development 

• Participate in code reviews, testing, and quality assurance processes. 

• Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services. 

• Develop algorithms to ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. 

• Document and communicate development processes and implementation details with peers and supervisors 

• Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. 

Required Qualifications: 

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related quantitative field. 

• 2+ years experience in the industry with a strong focus on ML solutions development and production deployment is a plus. 

• Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based LLM and MLMs, Boosted or standard decision trees, RAG, etc.  

• Strong grasp of OOP, Design Patterns, efficient algorithms, and quality software development. 

• Proficiency in Python and familiarity with ML libraries such as PyTorch. 

• Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemma etc. Some experience in developing and fine-tuning prompts on any of the GenAI services is a plus. 

• Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking. 

• The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment. 

• Good written communication skills that enable collaboration in a remote environment. 

Scale is a vital part of bringing AI-enabled technologies to the world, from autonomous driving to drones, robots, and large language models. For example, Scale works with the world's top self-driving car and robotics ML teams as well as the largest companies in the generative AI space. 

As our customer base is growing, you will be on the front lines of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers.

Our Field Engineers ensure customers' experiences with Scale's technology are seamless and optimized to build a successful, long-term partnership. Field Engineers partner closely with Product, Engineering, and Operations to lead existing customers through building production-grade data pipelines. We do this by knowing our customer’s use-cases inside and out, and creating the tooling and documentation needed to scalably support their growth.

Field Engineers in general are experts on Scale's products and codebase, and have general technical knowledge on web development, using APIs, and working with large volumes of data. Field Engineers are strong relationship builders, great project managers, and always fun to work with. 

The ideal person is a software engineer generalist who enjoys working with clients directly, taking ambiguous requirements and issues, and quickly designing and building sustainable solutions in close collaboration with the Product and Engineering teams. This role is at the intersection of customer delivery, product, and engineering, giving you a breadth of experience and fully leveraging both sides of your brain. If this sounds like you, we invite you to apply!

You will:

• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Work closely with our customer’s engineering teams to optimize data pipelines, including providing input towards designing API endpoints and input/output schemas
• Design, develop and maintain playbooks, internal tools, Scale’s documentation and SDKs to quickly get customers set up for long-term success
• Partner with Software Engineers and Operations to remove any technical hurdles customers may face / Debug technical issues impacting delivery and own technical escalations coming from the customer
• Be accountable for the customer’s technical experience throughout their time with Scale
• Work with AEs and PMs to identify customer-specific feature requests
• Develop technical domain expertise in areas of Large Language Models, 2D Image Annotation, and working with API integrations
• Evangelize Scale and interact with customers at major events
• Have an active TS/SCI clearance

Ideally you'd have:

• Track record of success as a hybrid customer-facing engineer or similar function, wearing multiple hats along the way
• Prior technical hands-on experience working with clients in a pre or post-sales capacity to realize business goals
• Prior experience developing with Python and JavaScript, or other modern software languages
• Strong engineering background preferably in Computer Science, Mathematics, or other quantitative fields
• Strong project management and interpersonal skills
• Presentation skills with a high degree of technical credibility when speaking with executives and front-line engineers
• High level of comfort communicating effectively across internal and external organizations
• Intellectual curiosity, empathy, and ability to operate with high velocity

Nice to haves:

• Experience in AI
• Experience working in classified environments
• Previous experience as a technical go-to-market resource
• Understanding of DevSecOps principles, including secure software delivery, infrastructure as code, and continuous integration/deployment
• Hands-on knowledge of container orchestration with Kubernetes and experience with Helm charts for application deployment
• Experience automating infrastructure and configuration management using Ansible or similar tools

ABOUT THE TEAM

Anduril's Air & Missile Defense Radar team develops cutting-edge tracking algorithms and software systems that detect, track, and characterize airborne threats in real-time. We're building the next generation of tracking intelligence capabilities—automated analysis systems that understand tracking performance, identify failure modes, and continuously improve our algorithms through data-driven insights.

This role sits at the intersection of ML engineering and tracking domain expertise. You'll build end-to-end pipelines that ingest tracking algorithm telemetry, analyze correlation failures and performance anomalies, train models to automate root cause analysis, and deploy production tools that help engineers ask questions like "why didn't track X and track Y associate?" We don't just track targets; we track our tracking systems and make them smarter.

WHAT YOU'LL DO

• Own tracking intelligence infrastructure end-to-end: Build the platform for ingesting tracking algorithm telemetry (hypotheses, scores, gains, association decisions), feature engineering performance metrics, training analysis models, and deploying them into production
• Automate tracking analysis: Develop ML models that identify correlation failures, track quality degradation, and root causes for tracking anomalies—replacing manual deep-dive investigations with scalable automated insights
• Build autotuning capabilities: Create systems that recognize incoming data characteristics and automatically adjust tracking algorithm parameters, frame rates, and model configurations for optimal performance
• Design human-in-the-loop tools: Build interfaces and query services that let engineers ask natural questions about tracking behavior and get data-driven answers backed by your models
• Exploit tracking telemetry: Instrument C++ tracking algorithms with appropriate logging (working with platform engineers), then marshal that data into consistent formats for analysis and model training
• Deploy in constrained environments: Package and deploy models for air-gapped systems with no external connectivity, following security scanning requirements where ML models are treated as data artifacts
• Manage the ML lifecycle: Handle data catalogs, ground truth labeling, model registries, versioning, and validation—ensuring models improve tracking performance in measurable ways
• Bridge domains: Translate between tracking algorithm fundamentals (Kalman filters, data association, multi-hypothesis tracking) and ML/data science techniques to build solutions that actually work
• Drive make/build decisions: Evaluate when to build custom models vs. leverage existing ML capabilities, selecting appropriate algorithm architectures for tracking intelligence problems
• Work hands-on-keyboard: This is a one-person show initially—you'll architect, code, deploy, and iterate rapidly using modern Python-based ML tooling

REQUIRED QUALIFICATIONS

• 3+ years of experience with a strong mix of ML engineering and data science—you've built models AND deployed them into production systems
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with MLOps practices: data pipelines, feature engineering, model versioning, experiment tracking, and deployment workflows
• Familiarity with ML infrastructure tooling (MLflow, Dagster/Airflow, or similar orchestration tools)
• Understanding of tracking, estimation, or filtering algorithms (Kalman filters, data association techniques)—you need to understand what tracking algorithms output and why they make the decisions they do
• Ability to work with streaming time-series data and engineer features from algorithm telemetry
• Experience building data catalogs, managing ground truth labels, and validating model performance
• Strong software engineering fundamentals—you can build maintainable, production-quality code independently
• Comfortable working in C++ environments enough to add instrumentation/logging (no deep algorithm development required)
• Ability to obtain and maintain a U.S. Top Secret SCI security clearance

PREFERRED QUALIFICATIONS

• Experience deploying ML models in edge, embedded, or air-gapped environments with security constraints
• Background in defense, aerospace, or sensor systems
• Familiarity with containerization (Docker, Kubernetes) for model serving and deployment
• Experience with anomaly detection, root cause analysis, or automated diagnostics systems
• Knowledge of AutoML, hyperparameter tuning, or online learning techniques
• Understanding of radar systems, sensor fusion, or signal processing
• Experience building conversational or query interfaces for technical systems
• Familiarity with model registries and model-as-data artifact management
• Experience with distributed data processing (Spark, Dask) for large-scale telemetry analysis
• Formal coursework or training in MLOps, data science, or estimation theory
• Active U.S. Top Secret SCI clearance

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization.

We're looking for a Senior Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and  building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges.

This role will be based out of North America in the PST and MST zones only.

The ideal candidate for this role will have

• 2+ years of  engineering experience in backend systems, distributed systems, or core platform development
• Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory management, and performance tuning
• Experience with streaming data platforms such as Apache Kafka and Change Data Capture (CDC) tools like Debezium
• Experience with relational data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc)
• Exposure to client-side technologies such as JavaScript and React is a plus
• Good understanding of algorithms, data structures and their time and space complexity
• Curiosity, a positive attitude, and a drive to continue learning
• Excellent verbal and written communication skills

Nice to Have

• Familiarity with cloud-native distributed systems (e.g., Kubernetes)
• Experience with NoSQL databases and understanding of their trade-offs is great, but not required. We'll teach you NoSQL
• Contributions to relevant open-source projects

Position Expectations

• Contribute high-quality, well-tested backend code to the data migration engine and core components of our generative AI orchestration platform
• Collaborate effectively with Product Management, AI researchers and machine learning engineers and designers to build and deliver on the product roadmap
• Work to develop robust and efficient backend services that orchestrate AI functionalities
• Identify and address performance bottlenecks and architectural challenges in our systems, particularly within data flow and orchestration
• Participate actively in code reviews to enforce best practices and patterns
• Help troubleshoot and resolve complex technical issues in our distributed systems
• Give and solicit feedback on technical design documents and pull requests
• Perform tasks related to process such as CI/CD, quality, testing, etc 

Success Measures

Within the first three months, you will have:

• Familiarize yourself with the MongoDB database and aggregation language
• Familiarize yourself with the backend tech stack including Java, Spring Boot, and Kafka
• Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks
• Started collaborating with your peers and contributed to code reviews

Within six months, you will have:

• Familiarised yourself with the rest of our the application modernization tool stack
• Delivered at least one large scale feature that spans the entire tech stack
• Reviewed and contributed to scope and technical design documents

Within 12 months, you will have:

• Become a key contributor to our backend stack, capable of taking on complex features independently
• Helped recruit and interview new members of the team
• Collaborated effectively with other teams at MongoDB on cross-functional projects

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

REQ ID: 425547

Tenstorrent is looking  for a STA methodology engineer who owns timing across advanced-node, high-performance, low-power designs, bringing deep expertise with PrimeTime, noise/crosstalk/OCV analysis, and strong scripting skills. They will lead the development and optimization of end-to-end STA methodologies and flows, drive data- and ML-assisted timing automation, and partner closely with logic, physical design, DFT, and EDA vendors to solve complex timing challenges across multiple IPs and products. 

This role is hybrid, based out of Santa Clara, CA, Austin, TX, or Fort Collins, CO.

We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting

Who you are

• An experienced Static Timing Analysis (STA) / timing methodology engineer with a BS/M in Electrical or Computer Engineering (or equivalent experience) 5+ years in industry, focused on high-performance and low-power designs at advanced technology nodes. As well as a deep knowledge of STA tools and techniques, including noise, crosstalk, and OCV analysis.
• You are fluent with PrimeTime and related signoff tools (e.g., PT-SI, PTPX, PT-ECO) and have extensive hands-on experience driving signoff correlation, advanced static timing analysis, and signoff closure.
• You are strong at debugging timing constraints, resolving timing correlation issues, and developing effective timing closure strategies.
• You write robust, production-quality scripts in Tcl, Python, and/or Perl and are comfortable building and maintaining CAD utilities and flow components.

What we need

• A senior methodology owner to lead cross-functional efforts to solve complex timing challenges across multiple IPs, projects, and technology nodes. Experience developing and enhancing STA methodologies across the full RTL-to-GDS flow, including: Early timing estimation and timing feasibility checks. Timing optimization techniques in synthesis and place-and-route. Timing signoff methodologies and criteria. Post-route timing ECO strategies and execution.
• A technical leader to architect, optimize, and maintain production STA flows using industry-standard EDA tools, continuously improving PPA (Power, Performance, Area) and runtime efficiency.
• A methodology engineer who can explore and deploy data-driven and ML-assisted techniques to: Improve STA automation. Predict and prioritize timing risk. Guide optimization strategies across blocks and full-chip. Design, implement, and maintain scalable CAD utilities and STA flow components that improve PPA, robustness, and team productivity.
• A methodology owner who continuously refines workflows and introduces new technologies to ensure robust, PPA-optimized timing solutions across all product lines.

What you will learn

• How to scale STA methodologies across a diverse portfolio of IP and SoC programs, balancing aggressive performance targets with strict power and area constraints.
• Best practices for integrating data-driven and ML-assisted approaches into timing flows to improve automation, predictability, and decision-making.
• How to influence tool roadmaps by partnering closely with leading EDA vendors on advanced-node timing, noise, and variability challenges.
• How to operate within and help shape a rapidly evolving startup design environment, including tradeoffs between quick solutions and long-term methodology investments.
• Deeper cross-functional insight into how logic design, physical design, and DFT interact with STA methodology, and how to build flows that serve all of these stakeholders effectively.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. 

Meet Slingshot 

At Slingshot Aerospace, we're on a mission to make space safer and more secure for everyone. Our work directly impacts global security, disaster response, climate monitoring, and the critical infrastructure that connects our world. We're a team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software. We move fast, we're not afraid to fail, and we believe the best ideas can come from anywhere—whether you're in engineering, sales, product, or operations. If you want to work on something that truly matters, with people who care deeply about the impact we're making and help shape the future of an industry that's just getting started, you're in the right place. 

What You’ll Be Launching 

As a member of Space Surveillance Research and Development (R&D) technical staff, you will support Slingshot’s efforts to accelerate the security, safety, and sustainability of space via the detection, tracking, identification, and characterization of satellites and space debris. This work will include a subset of (i) designing sensing systems for space surveillance applications; (ii) development of software/hardware interfaces for ground- and space-based gimbaled and non-gimbaled sensor systems, (iii) development of state-of-the-art detection, calibration, and mount control algorithms; (iv) modeling, simulation, and analysis of sensor network capabilities; and (v) development of robust software to process data from ground- and space-based SDA sensors. This role requires Top Secret clearance with SCI eligibility.

We're building a team of sharp, creative people who love solving hard problems. We value curiosity over ego, initiative over waiting for permission, and people who genuinely care about doing great work. Bring your expertise, your fresh ideas, and your drive—we'll bring the rocket fuel. 

Your Mission (Should you choose to accept it)  

• Execute all position responsibilities in alignment with Slingshot’s core values, mission, and purpose 
• Develop algorithms and software to help automate and enhance sensor data tasking, collection, processing, exploitation, and dissemination
• Perform system-level design, simulation, and integration of hardware components to create cutting-edge space surveillance systems
• Support ongoing and future transitions of Slingshot’s products and services to the Slingshot Global Sensor Network (SGSN), space operations centers, and other technology testbeds
• Engage with customers and stakeholders to ensure successful outcomes for their mission-critical needs
• Contribute your expertise and ideas to help shape our products and strategies
• Prepare technical reports and briefing materials
• Represent your team and Slingshot to a broader audience through presentations to customers and stakeholders
• Serve as a technical expert and key contributor to Slingshot’s space surveillance technology development
• Lead the successful execution of individual projects, small team projects, and/or product development activities
• Perform other duties as assigned (to be less than 10% of the responsibilities listed above) 
• Top Secret clearance with SCI eligibility is required for this role. 

Pre-flight Checklist 

• Undergraduate degree in Aerospace Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, Applied Mathematics, Physics, Astronomy, or a related field 
• 4+ years of relevant experience, potentially accounting for a record of academic excellence with relevant internship experience
• Experience developing applications in Python, C++, and Docker
• Effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike
• Demonstrated ability to work independently with little to no day-to-day oversight
• Ability to work in a SCIF in Colorado Springs, CO for up to 20 hours per week (remainder will be remote work-from-home)
• Tenacious drive to overcome challenges and deliver solutions with excellence 

Bonus Cargo 

• Graduate level degree in Aerospace Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, Applied Mathematics, Physics, Astronomy, or a related field 
• Significant experience developing and debugging applications in Python and/or C++ with deployment experience in a Linux operating environment
• Cislunar SSA experience
• Training or experience in fields such as orbital analysis, algorithm optimization, software/hardware interfacing, embedded/GPU development, astrodynamics, estimation theory, statistical analysis, remote sensing, radiometry, and machine learning
• Early-stage startup experience 

We're building a constellation here, not looking for identical satellites. Every member of the team brings different capabilities to the same mission. If your orbit intersects with ours and you're mission-ready, send it. 

Location: Hybrid Colorado Springs, CO Area (50% onsite in SCIF, 50% remote) 

Relocation: Relocation assistance available for qualified candidates

Salary: $127,500-$212,500

Classification: Full time Exempt (learned professional exemption) 

ABOUT THE TEAM

At Anduril, our Software Engineers specialize in solving complex, real-world problems through cutting-edge algorithms and intelligent software integrations. Operating in small, innovative teams, we push the boundaries of what's possible to deliver advanced technologies with mission-critical applications. Our commitment doesn't end with academic research or proof-of-concept experiments; we measure our success by the real-world impact of our deployed solutions. Inspired by Arthur C. Clarke's vision — "Any sufficiently advanced technology is indistinguishable from magic" — we aim to achieve groundbreaking results in target tracking, state estimation, and situational awareness. We are currently seeking highly talented technologists to join our mission and redefine the future of defense technology.
 

WHAT YOU WILL DO:

• Define and influence the direction of a small team, leveraging your subject-matter expertise in target tracking and state estimation.
• Architect, maintain, and evolve complex software systems, refactoring existing codebases to improve performance, maintainability, and scalability.
• Prototype and deploy state-of-the-art algorithms for tracking, multi-sensor data fusion, and state estimation in agile, iterative development environments.
• Develop high-performance Rust software for real-time systems, ranging from tactical implementations to simulation environments and decision support tools.
• Design and implement robust filters, estimators, and probabilistic reasoning systems that enable actionable insights from noisy, ambiguous, or incomplete sensor data.
• Apply software design patterns and architectural best practices to manage technical debt and guide the evolution of production systems over time.
• Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate the benefits of our technology.
• Drive customer success by customizing algorithms and software for mission-critical use cases, including real-time tracking and sensor fusion.
• Integrate tracking and estimation technologies into the broader software development lifecycle, from requirements definition through testing and optimization.
• Translate technical progress into clear, actionable insights for diverse stakeholders, including colleagues and end-users.

REQUIRED QUALIFICATIONS

• 8+ years of professional software engineering experience & a Bachelor's degree in mathematics, physics, engineering, or other technical field (advanced degree strongly preferred)
• Demonstrated experience managing and evolving software architecture in production environments, including refactoring legacy systems and managing technical debt.
• At least 2+ years working on a single codebase or product, maintaining and expanding it as requirements evolved.
• Strong understanding of software design patterns, architectural principles, and best practices for building maintainable, scalable systems (beyond basic syntax proficiency).
• Proficiency in algorithm design, software development, and statistical modeling; experience with Rust, C/C++, Python, and Matlab is a plus.
• Solid understanding of applied mathematics, including linear algebra, optimization, probability, and stochastic processes.
• Knowledge of signal processing techniques for interpreting diverse sensor data (e.g., radar, lidar, EO/IR).
• Familiarity with big data pipelines, NoSQL databases, and the efficient handling of large-scale sensor data.
• Ability to engineer robust systems for estimation theory, adaptive filtering, controls, and complex signal environments.
• Demonstrated ability to work across development lifecycles, from prototyping to optimizing production systems.
• Eligible to obtain and maintain an active U.S. Secret security clearance. 

PREFERRED QUALIFICATIONS

• Experience refactoring and modernizing Rust codebases in production environments.
• Track record of architectural decision-making and technical leadership on long-lived projects.
• Contributions to open-source Rust projects or the broader Rust ecosystem.
• Experience with concurrent and parallel programming patterns in Rust.
• Experience in state estimation, including Bayesian filtering, sensor fusion, and recursive estimation techniques.
• Background in machine learning as applied to target tracking and recognition, including clustering, classification, and anomaly detection techniques.
• Strong knowledge of target tracking techniques, such as Kalman filters, particle filters, and multi-target tracking algorithms (e.g., JPDA, MHT, or PHD filters).

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

ABOUT THE TEAM

Anduril's Software Engineers excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our software engineers build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Anduril is seeking talented “magicians” to join in our mission to expand the boundary of what’s possible. 

WHAT YOU WILL DO:

• Contribute to the direction of a small team with your expertise and ideas
• Prototype state-of-the-art software solutions in an agile development environment
• Implement high-performance software spanning the spectrum from tactical systems to web applications
• Use high-fidelity modeling and simulation environments, innovative analysis tools, and sound analysis techniques to quantify the benefit of our technology
• Engage with our customers, to ensure successful outcomes for their mission-critical needs
• Work with all aspects of the software development lifecycle
• Help your colleagues and customers understand what you’re doing and why

REQUIRED QUALIFICATIONS

• C/C++, Python, and Matlab;
• Big data/NoSQL/database technologies;
• AngularJS, Node.js, Javascript, and full-stack web development. 
• Software engineering: software design, algorithm implementation, and software analysis, testing, and optimization;
• Machine learning: supervised and unsupervised learning, clustering, and classification;
• Applied mathematics: differential equations, linear algebra, optimization, statistics, and random processes;
• Engineering: controls, estimation theory, and digital signal processing.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

ABOUT THE TEAM

The Anduril Battlespace Awareness Radar team develops state-of-the-art radar systems, deployed to tackle the most significant security challenges of America and its allies.

ABOUT THE JOB

We are looking to hire a Systems Engineer to join our rapidly growing team in Broomfield, CO. The Battlespace Awareness team develops tactical sense- and decision-making software that provides advanced capabilities for Anduril's command and control (C2) products. This software must work with various combinations of compute hardware, connected sensor/effector hardware, and supporting software services.  It must be effective, robust, and safe across various configurations, mission sets, and customer experiences. We need systems engineers who are capable of internalizing the nuances of these complex systems, and ensuring the technical success of an end-to-end solution. 

WHAT YOU’LL DO

The Systems Engineer will support the design, development, and validation of advanced algorithmic capabilities including tracking, sensor/effector management, battlespace optimization, and threat forecasting.  This role bridges system design, requirements management, modeling and simulation (M&S), and verification & validation (V&V) activities.  You will integrate emerging capabilities into new products and system configurations.  You will lead requirements decomposition across cross-functional teams, defining success in the face of ambiguity. You will develop test plans, acceptance criteria, and analysis tools to evaluate system performance using both simulation and collected field data.   You will use data-driven analysis to verify customer requirements are met, and create artifacts to trace performance as the system evolves  You will own systems end-to-end, bringing an ability to identify and solve problems between the seams and push through to reach an ultimate desired outcome. 

• Lead the integration of emerging capabilities, bringing new products into the family of systems. This may include scoping and executing on a combination of hardware and software solutions, both internal and external to the company.
• Lead requirements decomposition across cross-functional teams, defining success in the face of ambiguity.
• Responsible for scoping ideal system laydown, scrutinizing system performance, and ensuring the deployed system is meeting customer requirements.
• Also responsible for making tradeoffs across capability, timelines, risk, cost, and other factors to deliver an outcome. 
• Own systems end to end with the ability to identify and solve problems between the seams and push through to reach an ultimate outcome.

REQUIRED QUALIFICATIONS

• 2-4 years of hardware and software systems engineering experience. Degree in Engineering, Physics, Robotics, Mathematics, or a related field. 
• Demonstrated use of model based systems engineering in program lifecycle. Experience with tools such as: JAMA, Cameo, Matlab, Simulink, AFSIM.
• Proficiency with programming languages such as Python for data parsing, modeling & simulation, data analysis, and visualization. 
• Skilled in Statistics, AI/ML, Requirements, Testing, MBSE.
• Demonstrated proficiency in the application of engineering standards into engineering processes or requirements.
• Demonstrated experience collaborating across cross-functional teams.
• Ability to communicate complex technical findings clearly to developers, system leads, and customers.
• Comfortable working with ambiguity, evolving priorities, and challenging problems.
• Experience conducting system and software-level hazard analyses (e.g., Functional Hazard Analysis) to identify potential failures and define risk mitigation strategies.
• Familiarity with DoD System safety standards such as MIL-STD-882E
• Skilled in working software developers and QA teams to review software architecture, design, and code against safety principles and contribute to the maintenance of the system hazard log.
• Eligible to obtain and maintain an active U.S. Secret security clearance
• Up to 25% travel to customer sites.

PREFERRED QUALIFICATIONS

• Familiarity with Linux OS.
• Familiarity with processes and constraints for real-time and safety-critical software.
• Working knowledge of C/C++ or Rust (coding full-time is not required but understanding is valuable)
• Understanding of the full software development lifecycle.
• Prior involvement in field exercises, test events, experimentation campaigns.
• Comfortable obtaining data from software platforms using command-line tools.
• Previous experience in a defense, aerospace, or naval environment.
• Experience with any of the following: radar, optics, tracking systems, distributed systems, autonomous systems, computer vision, wireless communication, software defined radios, networking. 

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

ABOUT THE TEAM

Anduril's Air & Missile Defense Radar team develops cutting-edge tracking algorithms and software systems that detect, track, and characterize airborne threats in real-time. Working in small, focused teams, our software engineers design and implement sophisticated tracking solutions that protect lives and critical assets. Our work spans the full spectrum—from developing novel multi-target tracking algorithms to building high-performance distributed systems that process massive amounts of sensor data in milliseconds

We don't just publish papers; we deploy production-grade systems that our government and industry customers depend on for mission-critical operations. If you're passionate about applying mathematics, software engineering, and signal processing to solve complex real-world problems, we want to hear from you.

WHAT YOU WILL DO

• Design and implement advanced tracking algorithms for novel air and missile threats, including multi-target tracking, track fusion, and discrimination techniques
• Develop high-performance, real-time software systems that process radar sensor data and maintain tracks on dozens to hundreds of simultaneous targets
• Build and leverage modeling & simulation environments to validate tracking performance, quantify system capabilities, and identify areas for improvement
• Collaborate directly with radar engineers and system architects to integrate tracking solutions into end-to-end defense systems
• Optimize tracking software for performance-critical environments where milliseconds matter
• Communicate technical concepts and trade-offs to cross-functional teams, program leadership, and customers to drive informed decisions
• Participate in customer demonstrations and field tests to ensure successful deployment and operational effectiveness

REQUIRED QUALIFICATIONS

• 2 years of relevant experience & Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or related technical field (or equivalent experience)
• Strong programming skills in C++ and Python
• Solid foundation in mathematics: linear algebra, probability, statistics, and/or differential equations
• Understanding of software engineering fundamentals: design patterns, testing, version control, and debugging
• Ability to obtain and maintain a U.S. Top Secret SCI security clearance

DESIRED QUALIFICATIONS

• Experience with tracking, estimation, or filtering algorithms (Kalman filters, particle filters, multiple hypothesis tracking, etc.)
• Background in controls, estimation theory, or digital signal processing
• Familiarity with radar systems or sensor fusion
• Experience with high-performance computing (multithreading, GPU acceleration, distributed systems)
• Knowledge of machine learning techniques for classification, clustering, or data association
• Proficiency with database technologies (SQL, NoSQL, time-series databases)
• Experience with web development technologies (JavaScript, React, Node.js) for building visualization and analysis tools
• Familiarity with modeling and simulation tools (MATLAB, Simulink, or custom frameworks)
• Experience working in agile development environments
• Active U.S. Top Secret SCI clearance

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

ABOUT THE TEAM

Anduril's Software Engineers excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our software engineers build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Anduril is seeking talented “magicians” to join in our mission to expand the boundary of what’s possible. 

WHAT YOU WILL DO:

• Contribute to the direction of a small team with your expertise and ideas
• Prototype state-of-the-art software solutions in an agile development environment
• Implement high-performance software spanning the spectrum from tactical systems to web applications
• Use high-fidelity modeling and simulation environments, innovative analysis tools, and sound analysis techniques to quantify the benefit of our technology
• Engage with our customers, to ensure successful outcomes for their mission-critical needs
• Work with all aspects of the software development lifecycle
• Help your colleagues and customers understand what you’re doing and why

REQUIRED QUALIFICATIONS

• 8+ years of experience and a Bachelors degree or equivalent education/work experience
• C/C++ and Python
• Big data/NoSQL/database technologies;
• Software engineering: software design, algorithm implementation, and software analysis, testing, and optimization;
• Machine learning: supervised and unsupervised learning, clustering, and classification;
• Applied mathematics: differential equations, linear algebra, optimization, statistics, and random processes;
• Engineering: controls, estimation theory, and digital signal processing.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.

Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team.

This role is hybrid, based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. 

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts.
• Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration.
• Strong problem solver who excels at debugging complex issues across design hierarchies.
• Collaborative team player who thrives in fast-paced, technically challenging environments.

Tenstorrent is seeking a talented Physical Design Engineer to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team.

This role is hybrid, based out of Austin, TX or Santa Clara, CA or Fort Collins, CO.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts.
• Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration.
• Strong problem solver who excels at debugging complex issues across design hierarchies.
• Collaborative team player who thrives in fast-paced, technically challenging environments.

What We Need

• BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs.
• Expertise with industry-standard tools (FusionCompiler, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python).
• Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling).
• Experience driving physical design requirements from early architecture through final signoff.

What You Will Learn

• How to implement cutting-edge AI accelerators, high-performance CPUs and the SOCs that host them on the most advanced process nodes.
• Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures.
• End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams.
• Direct impact on products that are redefining the landscape of AI and high-performance computing.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Tenstorrent is seeking an Physical Design Engineer to lead  cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. 

This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who you are

• BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes.
• Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs.
• Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows.
• Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.

What we need

• Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.
• Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.
• Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.
• Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.

What you will learn

• How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows.
• New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits.
• Best practices for deploying, validating, and monitoring ML models in production CAD environments.
• How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. 

Hudson River Trading (HRT) is seeking a Physical Design Engineer with a broad, versatile skillset to join our growing Hardware team. In this role, you will help deliver performance-critical ASICs and advance our physical design methodologies on leading-edge process nodes.

The Hardware team at HRT builds high-performance compute engines using FPGA and ASIC technology to drive low-latency trading decisions on global markets. We create custom solutions across the full spectrum of speed and sophistication, from bespoke circuits to world-class machine learning accelerators.

Responsibilities

• Drive design-for-test (DFT) methodologies and implementation 
• Contribute to physical implementation, from RTL handoff through GDSII on advanced process nodes 
• Partner on floorplanning and physical optimization for high-performance, latency-critical designs
• Close timing across multiple modes and corners while optimizing power, performance, and area (PPA)
• Diagnose and resolve physical design issues such as timing bottlenecks, congestion, and IR/EM violations
• Build, maintain, and improve repeatable, automated physical design flows
• Develop scripts and tooling to improve productivity, robustness, and insight into design behavior
• Collaborate closely with RTL, architecture, and other hardware engineers to influence design decisions early

Qualifications

• Experience working in high-performance ASIC design environments
• Strong fundamentals in digital logic, circuit design, and process technology
• Familiarity with DFT concepts and testing methodologies
• Strong scripting and automation skills (Python, Tcl, shell), including parsing and analyzing tool outputs
• Ability to design robust methodologies, diagnose complex failures, and improve physical design flows
• Applied use of statistics in analyzing timing, power, or design data (preferred)
• Hands-on experience with static timing analysis and timing closure methodologies
• Expertise using industry-standard physical design and signoff tools (e.g., Innovus, PrimeTime)

This job is accepting ongoing applications and there is no application deadline.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience.

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

The Hardware team at Hudson River Trading (HRT) creates high performance compute engines using FPGA and ASIC technology to drive low latency trading decisions on global markets. We build custom solutions across the spectrum of speed and smarts: from bespoke circuits to world-class machine learning accelerators.

These high performance designs require even higher performance verification. We are looking for experienced Design Verification (DV) engineers who are skilled at writing testbenches and building verification environments to exercise complex HDL. Our ideal candidate is not only an ace tester, but a practicing toolsmith. You know the EDA landscape and want to be part of a team actively working to rethink, redesign, and surpass the status quo. For example, members of our team are active maintainers of popular open source projects such as Slang, Verilator, and Cocotb.

FPGA and ASIC verification is part of an innovative, growing team at HRT which is integral to the success of our trading. You can expect to always be challenged by the ever-changing financial markets as you work to ensure correctness and robustness of our critical hardware in an extremely fast-paced, real-time environment. No financial experience is necessary.

Responsibilities

• Creating testbenches and tests for our hardware platform, leveraging a hybrid open-source/proprietary, highly flexible environment
• Writing detailed verification plans
• Quickly root-cause RTL bugs
• Collaborating directly with designers for rapid bringup of new projects and debugging of existing designs
• Managing test suites and continuous integration infrastructure
• Developing and improving open-source and internal tools

Qualifications 

• Superb debug and analytical skills 
• Professional experience (2+ years) in RTL functional verification for FPGA or ASIC
• Experience with code and functional coverage collection/analysis
• Experience with SystemVerilog and industry-standard frameworks such as UVM
• Experience with Python
• Comfortable in a Linux environment
• Familiarity with Verilator and/or Cocotb preferred
• C++ experience is a plus
• A bachelor’s degree in computer science, electrical engineering, or a related field

The estimated base salary range for this position is 175,000 to 250,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

The Hardware team at Hudson River Trading (HRT) creates high performance compute engines using FPGA and ASIC technology to drive low latency trading decisions on global markets. We build custom solutions across the spectrum of speed and smarts: from bespoke circuits to world-class machine learning accelerators.

FPGAs and ASICs are critical pieces of our technology stack. We are looking for talented hardware developers to architect and design complex systems on a highly collaborative global team. In this role, you'll identify efficient ways to perform on-the-fly transformations of market data and implement models with complex data structures in RTL. Deep knowledge of SystemVerilog, FPGA internals and/or ASIC primitives, computer architecture, and vendor tool suites are essential to succeeding in this role. Expertise in networking protocols, CPU design, and/or machine learning accelerators is a big plus. No financial experience is necessary.

Responsibilities

• Collaborate with a cross-functional team to develop and deploy custom FPGA and/or ASIC solutions for a wide range of trading applications
• Investigate new technologies and tools
• Contribute to a nimble hardware development tech stack

Qualifications

• Ability to describe hardware designs at a high level, low level, or anywhere in between
• Brilliant design, optimization, debugging and problem solving skills
• Professional experience (2+ years) in RTL design for FPGA or ASIC
• Expert SystemVerilog development skills with a thorough understanding of the language 
• Expert on low level FPGA or ASIC architectures, with a deep understanding of what makes them "tick"
• Skilled in network communications, processing pipelines, and/or machine learning
• Working knowledge of Python and/or C++
• Comfortable in a Linux environment
• Strong verification experience
• Familiarity with AMD Vivado is a plus
• A bachelor’s degree in computer science, electrical engineering, or a related field

This job is accepting ongoing applications and there is no application deadline.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience.

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

What You'll Do 

1. Design and implement containerized microservices within an AWS environment (Lambda, ECS)
2. Lead the design of relational database schemas (Postgres), prioritizing query performance engineering and indexing strategies to handle large, readily available SDA datasets
3. Own the end-to-end feature development and integration of streaming and batch ETL pipelines
4. Familiarity with deploying ML models in production and adding instrumentation to monitor model performance
5. Help with architecture design and defining technical direction
6. Mentor and help develop other less experienced engineers 

What We Value:

1. Strong ownership mentality – you’ll lead technical execution and ensure your features make it from development to production
2. Accountable – The team knows they’ll be able to depend on you
3. Curiosity – We are solving the hardest problems in space and want to hear everyone’s voice to ensure we’re always innovating
4. Leadership – You will be on a small team and will be empowered to help grow the culture and influence technical direction 

Your Ideal Background:

Required:

1. 5+ years of full-time software engineering experience
2. Experience working in the defense/space industry
3. Comfortable working in a small, fast-paced Agile environment
4. Strong communication skills and ability to execute under uncertainty
5. Familiarity with one or more of the following: Machine Learning, SDA, Backend Development
6. Proficiency in Linux, Python, SQL, Docker, and AWS
7. Eligible to obtain and maintain an active U.S. security clearance 

Nice to Have: 

1. Experience instrumenting microservices with Observability (we use the LGTM stack)
2. Comfortable leading algorithm development across different SDA data modalities (EO, Orbital, RF, etc.) to solve problems such as anomaly detection, pattern-of-life modeling, or maneuver detection 

Compensation and Benefits:  

Your base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.  The anticipated salary range for this role is $150,000 - $190,000 annually.

Base salary is just one part of your total rewards package at Katalyst. You will also be eligible for long-term incentives, in the form of the Employee Stock Option and Equity Plan, as well as a relocation bonus and other discretionary bonuses. You will also receive access to comprehensive medical, vision, and dental coverage, and unlimited Paid Time Off.

At Katalyst our work on projects involving the U.S. Department of Defense requires adherence to International Traffic in Arms Regulations (ITAR), 22 C.F.R. Parts 120-130, which requires compliance with U.S. export laws before allowing employees to perform certain positions. Currently, our available roles necessitate access to ITAR-controlled information, and as a result, Katalyst would have to ensure any non-US person is authorized access to ITAR information before the commencement of employment. We are committed to equal employment opportunities and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

*remote work will require an exception from the hiring team

Our Senior Developer Advocates are technical leaders and mentors that anchor our team. They own projects from beginning to end, facilitating collaboration and enabling Datadog's community to solve real-world problems. With a focus on Data Observability, this role will enable our community of engineers around Datadog to be part of a movement of building better software. This is a unique opportunity to use both your engineering expertise and advocacy skills to shape the ever-evolving technological landscape.

What You’ll Do:

• Act as a subject matter expert for data observability on behalf of the Datadog advocacy and engineering teams
• Create content in one or more mediums to build Datadog's reputation as a leader in data engineering and observability e.g. building demos, public speaking, blogging, documentation, webinars, open source, research reports and more
• Partner with and coach internal product and customer engineering teams on effective public communication and presentations for the work they do
• Contribute to the product through feedback (bugs or product enhancements suggestions)
• Identify and pursue opportunities for events, programs, and other community-focused work that establishes trust with practitioners

Who You Are: 

You are a trusted technical expert who enjoys helping data practitioners understand, operate, and improve complex data systems in production. You bring deep, hands-on experience in one or more areas of modern data engineering, and you use that experience to provide clear context to both the community and internal teams.

You are not expected to be an expert in every area below. Instead, you bring depth in some and working familiarity across many, and you are comfortable connecting them into a coherent operational story.

• Data engineering & processing systems: You have built, operated, or supported production data pipelines using distributed processing systems such as Apache Spark or Databricks, and understand common failure modes, performance tradeoffs, and operational challenges in batch and hybrid pipelines.
• Data platforms & analytics systems: You have hands-on experience with analytics platforms such as Snowflake and BigQuery, including schema design, data modeling, SQL-based analysis, and reasoning about performance, cost, and access patterns in real-world environments.
• Streaming & event-driven data: You understand how data flows through streaming systems such as Kafka or similar platforms, including producer and consumer behavior, lag, delivery semantics, and how streaming issues propagate into downstream datasets and analytics.
• Data quality, lineage, and metadata concepts: You are familiar with how data teams reason about data quality, upstream and downstream impact, and change management, and have experience working with data lineage, metadata, or transformation tooling (for example dbt, OpenLineage, or related ecosystems), or have operated in environments where these concepts are core to reliability.
• Programming & querying: You are comfortable working in at least one programming language commonly used in data systems (for example Python, Scala, Java, or Go), along with strong SQL skills, and you can move fluidly between code, queries, and notebooks when exploring or demonstrating data systems.

You also have:

• 10+ years of experience as a software developer, data engineer, SRE, or other practitioner building and maintaining production systems
• 3+ years of experience in advocacy, developer relations, or equivalent experience reaching technical audiences through written content, conference talks, workshops, webinars, videos, or open-source contributions
• Publicly available writing samples, demos, repositories, or recordings of technical presentations
• Familiarity with modern cloud infrastructure and container-based systems
• A strong interest in self-directed learning and exploring new technologies, tools, and problem spaces

Bonus points:

• Experience supporting data pipelines for ML or AI systems
• Meaningful contributions to open source or shared technical tooling
  
  

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. 

Benefits and Growth: 

• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our Internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• Competitive global benefits

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Remote

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

About the role: 

As a Infrastructure Engineer - Systems you will provide the United States Space Force (USSF) Systems Engineering and Technical Assistance (SETA) for the Defensive Cyber Operations – Space (DCO-S) program by developing software in support of Space Systems Command (SSC) Cyber Operations Branch rapid agile development of defensive cyber solutions to protect, defend, and respond to both ground and space based cyber adversarial threats.

Core Responsibilities:

• Architectural Design: Develop and analyze complex system topologies and end-to-end architectures to ensure seamless integration of defensive cyber capabilities across ground and space segments.
• Infrastructure Planning: Lead the development of detailed Bills of Materials (BOMs) and rack diagrams, ensuring all hardware and software components are optimized for mission success and technical refreshes.
• Technical Consultative Leadership: Serve as the subject matter expert in high-stakes stakeholder meetings, answering complex technical questions and vetting the feasibility of proposed cyber solutions.
• System Surveys & Requirements: Assist with network tap design and system surveys to ensure data is properly sampled and transported, translating these findings into actionable engineering plans.
• Documentation & Redlines: Review and provide expert feedback on installation and configuration guides, ensuring technical accuracy through redlines and continuous documentation improvement.
• Deployment Oversight: Lead hardware installation and software deployment strategies at mission system sites, coordinating the efforts of technical teams without necessarily being the primary keyboard operator.
  
  

What we are looking for: 

• Experience: Minimum of 10 years of relevant experience in System Administration (Linux/Windows) or Systems Engineering with a master’s degree in a relevant field. In lieu of a master’s a bachelor’s with 18 years of experience is acceptable.
• Architectural Mastery: Proven ability to develop and analyze network topologies, data flow diagrams, and detailed rack integration plans.
• Technical Breadth: Strong knowledge of ESXi/VMware, Gigamon, Trellix, and containerization technologies (Kubernetes/Docker) to effectively guide implementation teams.
• Strategic Planning: Expert-level experience in building BOMs and managing the technical lifecycle of hardware/software stacks.
• Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and military leadership.
• Certifications: Security+ (required); CCNA, CCNP, or JNCIS-Sec (highly preferred).
• Tools: Experience with JIRA, Confluence, and collaborative environments (Slack/Mattermost)

Highly Preferred:

• Strategic Frameworks: Experience with Requirements Analysis, Scaled Agile Framework (SAFe), and Risk Management.
  
• Domain Expertise: Prior experience supporting Space Systems Command (SSC) or the Cyber Operations Branch.
• Mentorship: A proven track record of guiding technical teams and mentoring junior engineers through complex project lifecycles.

Clearance Requirements:

• Active Secret Security Clearance

Salary Range: $120,000.00 - $170,000.00

Work Type:

• Onsite in Colorado Springs, CO
• May require up to 25% travel

What we will offer you: 

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

About the role: 

As a Cyber Security Engineer, you will be responsible for architecting, planning, configuring, deploying, maintaining, and upgrading COTS/GOTS and custom toolsets to address vulnerabilities and/or implement security controls in order to secure DoD Risk Management Framework (RMF) cybersecurity approvals. You will apply a combination of expert engineering knowledge of enterprise IT and security solutions to design, develop and/or implement solutions to ensure they are consistent with enterprise architecture security policies and support full spectrum military cyberspace operations.

What you will do:

• Design, test, and implement secure operating systems, networks, security monitoring, tuning and management of IT security systems and applications, incident response, digital forensics, loss prevention, and eDiscovery actions
• Security control design and solution planning at the system, mission, and enterprise level, security-in-depth/defense-in-depth, and other related IAM/ISSO/ISSE support functions
• Involved in a wide range of security issues including architectures, firewalls, electronic data traffic, and network

What We Are Looking For 

• Bachelor’s degree with 14+ years of related experience, or Master’s degree with 12+ years, or PhD with 9+ years. Experience with cloud-native cybersecurity (i.e. Amazon Web Services and Microsoft Azure)
• Experience with cyber capabilities, TS clearance with SCI eligibility, applicable security training and certificates, cyberspace operations tactics, crisis action planning, and analytical methodologies

Highly Preferred

• Experience supporting DoD, federal, or classified software programs
• Familiarity with systems engineering processes and documentation
• Exposure to DevSecOps, CI/CD pipelines, or modern software delivery practices
• Experience with DoD cloud environments and processes
• Mentorship of junior engineers or informal technical leadership experience

Clearance Requirements:

• Active Top Secret with SCI 

Work Type:

• Onsite in Colorado Springs, CO 
• May require up to 15% travel

Salary Range: $140,000 - $170,000

• The determination of compensation is predicated upon a candidate's comprehensive experience, demonstrated skill, and proven abilities

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

About the role:

As a Principal Software Developer, you will serve as a senior technical authority responsible for defining, guiding, and validating software solutions for large-scale, mission-critical systems. You will lead technical planning, architecture decisions, and system integration efforts across programs while influencing engineering best practices and long-term technical direction.This role demands deep technical expertise, strategic thinking, and the ability to lead teams

This role requires deep hands-on expertise and the ability to collaborate closely with systems engineers, testers, and stakeholders to deliver high-quality software in structured or regulated environments.

Key Responsibilities: 

• Lead technical planning and execution for complex software systems and subsystems
• Define and validate high-level and detailed software requirements across programs
• Architect and guide software solutions aligned with mission, operational, and enterprise needs
• Oversee and direct test planning and execution, including:
  • Use case development
  • Test strategy, procedures, and test data
  • System-level validation and verification
• Lead software systems integration across platforms and environments
• Provide senior-level technical oversight across the full software lifecycle, including:
  • Concept design
  • Development and integration
  • Installation and deployment
  • Operations, sustainment, and modernization
  • Retirement and disposal
• Conduct and guide technical trade studies and architectural decision analysis
• Resolve the most complex software integration and performance challenges
• Mentor senior and mid-level developers and guide technical teams
• Ensure software solutions balance performance, security, schedule, and cost constraints
• Serve as a trusted technical advisor to program leadership and stakeholders

What we are looking for: 

• Bachelor’s degree with 18+ years of related experience, or
  Master’s degree with 16+ years, or PhD with 15+ years
• Expert-level experience in software architecture, development, systems integration and AWS tools
• Proven ability to lead complex technical efforts and guide engineering teams
• Extensive experience in requirements definition, system design, and validation
• Strong background supporting large-scale or mission-critical software systems
• Ability to influence technical direction across programs or organizations

Highly preferred: 

• Technical leadership experience on DoD, federal, or classified programs
• Deep familiarity with systems engineering methodologies and lifecycle processes
• Experience defining engineering standards, best practices, or reference architectures
• Formal mentorship or team leadership responsibilities
• Experience supporting highly regulated or high-assurance environments

Clearance Requirements:

• Active Top Secret with ability to obtain and maintain SCI 

Work Type:

• Onsite in Colorado Springs, CO
• May require up to 15% travel

Salary Range:

• $165,000 - $210,000
• The determination of compensation is predicated upon a candidate's comprehensive experience, demonstrated skill, and proven abilities

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

About the Opportunity

We are seeking a Senior Software Engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package, test, orchestrate, deploy, and maintain ML models, improve workflows, and implement CI/CD and automated testing to ensure reliability, performance, and faster delivery of business value.

Responsibilities

• Design, build, and deploy scalable AI/ML services with clear service boundaries, making pragmatic trade-offs across performance, maintainability, security, and long-term extensibility.

• Own full lifecycle delivery of complex features from architectural planning and API design to implementation and post-release observability.

• Define and enforce robust verification and validation for AI services including unit, integration, and end-to-end testing to ensure reliability of code in production and compliance with our Quality Management System and regulatory standards. 

• Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment.

• Translate product requirements into well-defined technical designs proactively shaping implementation details.

• Contribute to the necessary technical documentation required for regulatory submissions.

• Collaborate cross functionally to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation. 

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

• 7+ years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).

• Experience with unit, integration testing for ML models, including data validation, correctness checks, and reproducibility.

• Experience with CI/CD, Orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms(SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark) to build scalable ML data pipelines and model workflows.

• Strong collaboration skills to work effectively with ML scientists, engineers, and regulatory teams.

• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $153,000 - $179,000
• TTC: $176,000 - $206,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

About the Opportunity

We are seeking a senior machine learning software engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package, test, orchestrate, deploy, and maintain ML models, improve workflows, and implement CI/CD and automated testing to ensure reliability, performance, and faster delivery of business value.

Responsibilities

• Collaborate with AI scientists to package and deploy ML models, ensuring reproducibility, versioning, and compliance.
• Build and maintain model serving infrastructure including monitoring, drift detection, automated retraining, and logging.
• Implement unit, integration, and system-level testing for ML models, covering data validation, model correctness, and deployment workflows.
• Develop and operate end-to-end ML pipelines: ingestion → preprocessing → feature engineering → evaluation → deployment → monitoring.
• Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment.
• Identify and resolve workflow inefficiencies or gaps between research and production.
• Recommend and integrate frameworks, libraries, and infrastructure to improve pipeline efficiency, maintainability, and observability.
• Collaborate cross-functionally to ensure compliance with regulatory requirements (FDA/HIPAA) in production ML workflows.
  
  

Requirements

• 7+ years of experience in software engineering for ML production or ML platform delivery.
• Hands-on experience deploying ML models via APIs, batch pipelines, or streaming inference.
• Proficiency in Python (required), Java, or similar, with software engineering best practices for ML workflows.
• Experience with unit, integration, and pipeline-level testing for ML models, including data validation, correctness checks, and reproducibility.
• Familiarity with cloud platforms (AWS preferred: SageMaker, S3, EC2) and reproducible ML pipelines.
• Experience with CI/CD, Orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms(SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark) to build scalable ML data pipelines and model workflows.
• Strong collaboration skills to work effectively with AI scientists, software engineers, and regulatory teams.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $153,000 - $179,000
• TTC: $176,000 - $206,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

About the Role

We are seeking a strong Senior Data Engineer to build and maintain scalable, high-quality data pipelines powering Checkr’s centralized data platform. As a Senior Engineer, you will independently deliver complex features, contribute to system design, and collaborate with cross-functional partners to support the next generation of our data products.

What You’ll Do

• Independently design and implement complex batch and streaming pipelines using PySpark, SQL, and AWS services.
• Navigate ambiguity with guidance, translating high-level direction into well-scoped, high-quality technical solutions.
• Work cross-functionally with product, design, analysts, and engineers to ship impactful features and improve data workflows.
• Contribute to architectural discussions and system improvements without owning long-term strategy.
• Ensure pipeline reliability and data quality, implementing testing, monitoring, and observability best practices.
• Investigate and resolve production issues for services owned by the team.
• Write performant, maintainable code that aligns with engineering standards.
• Support the team in building foundational datasets that enable analytics, ML, and customer-facing features.

What You Bring

• 6–7+ years of experience in data engineering with strong hands-on execution ability.
• Proficiency with PySpark, Python, and SQL, including debugging and performance optimization.
• Experience building large-scale pipelines (up to terabytes or larger), with exposure to streaming systems such as Kafka.
• Strong knowledge of data modeling, relational databases, and NoSQL stores.
• Experience with AWS services such as EMR, Glue, Athena, Lambda, and S3.
• Exposure to Iceberg or other lakehouse technologies (nice to have).
• Understanding of security and data privacy fundamentals.
• Strong problem-solving skills, attention to detail, and ability to execute independently.
• Knowledge of Databricks, Snowflake, or Graph/Vector stores is a plus.

Spire is making a fundamental shift in how it operates its constellation. We are moving from a model where trained operators watch dashboards and escalate to experts, to one where the system is fully autonomous, self-healing, and data intelligent. This team is building that future, and this role sits at the center of it. 

The old model relies on operators, escalations, manual processes, and institutional knowledge locked in the heads of a few experts. It does not scale and it does not belong in a modern space company. We know what we want to replace it with: SRE principles applied to a constellation, autonomous fault handling, AI-driven anomaly detection, low toil, high data quality, and continuous improvement baked into the system. 

You will be one of the engineers who makes that real. 

What You Will Work On  

Autonomous Operations: 

• Design and build fault detection, isolation, and automated recovery pipelines for satellites and ground stations
• Drive elimination of manual processes. If a human is doing it repeatedly, automate it.
• Build space situational awareness systems so the fleet always knows its own state
• Develop operational automation for mission execution at scale

Telemetry and Data Platform: 

• Architect and build a flexible data platform that ingests, stores, and surfaces telemetry from space and ground assets
• Build analytics and visualization tools that surface operational insight and not just raw data
• Apply ML and AI techniques to detect anomalies, predict failures, and optimize constellation performance
• Work directly with data at every layer from pipeline design to query

Reliability Engineering: 

• Define and instrument SLOs and reliability metrics for space and ground assets
• Build monitoring and alerting systems that know what matters and ruthlessly suppress noise
• Own configuration control and software rollout processes for on-orbit and ground assets

Mission Software: 

• Build real-time dashboards and operator tooling that make mission status immediately legible
• Collaborate directly with satellite operators and mission teams to turn operational pain into software solutions
• Design systems for automated mission execution including planning, scheduling, and commanding at scale

Basic Qualifications

• 5+ years of professional software engineering, SRE, or DevOps experience
• Strong Python skills across backend services, data pipelines, and automation. Not just scripts.
• Real experience applying data analysis to solve complex operational or technical problems, comfortable working directly with data at every layer from pipeline design to query
• Solid Linux fundamentals including bash scripting and basic system administration
• Experience with containerized development and production environments
• The communication skills to work across engineering, operations, and mission teams and translate real-world requirements into working software

Preferred Qualifications

• Experience with data backends such as Postgres, Redis, Elasticsearch, or S3
• Hands-on experience with Databricks or modern data Lakehouse tooling
• Experience building or operating monitoring and alerting systems such as Grafana, Prometheus, or Nagios
• Infrastructure as Code experience with tools such as Terraform or Ansible
• ML or AI applications in an operational or monitoring context
• Experience with Python data visualization libraries

Spire operates a hybrid work model, and this position will require you to work a minimum of three business days per week in the office.

Access to US export-controlled software and/or technology may be required for this role. If needed, Spire will arrange the necessary licenses—this is not something candidates need to have before applying. _#LI-MK1

About your role

Rocket Lawyer is seeking an experienced, passionate AI/ML software engineer for Rocket Copilot, our new AI assistant launched in December 2023. In this role, you will help our team deeply embed AI features across our platform. You will work in an agile, cross-functional team, working with multiple product teams as we build out AI features across Rocket Lawyer. You will design, implement, test, release and maintain new AI features, working closely with product managers, UX designers, data engineers, QA engineers, and others.

We value a fun, collaborative, team-oriented work environment, where we celebrate our accomplishments. 

How you will make a difference day to day

• Build, train, fine-tune, deploy and maintain ML models for AI features
• Create, monitor and troubleshoot backend API services to allow Rocket Lawyer product frontends to interact with ML models
• Work closely with multiple product teams and cross-functional teammates to quickly integrate AI into existing and new Rocket Lawyer products
• Keep up-to-date with industry trends around generative AI and machine learning
• Rapidly prototype product features to explore new AI capabilities, while writing clean, understandable code

What you’ll need

• 5+ years of Experience writing ML code for launched products
• Understanding of the state of the art in generative AI, including RAG, LoRA, RLHF and others
• Experience creating data sets from proprietary anonymized data, and using them to train and fine-tune ML models
• Experience with machine learning frameworks like TensorFlow, PyTorch and Scikit-Learn
• Strong programming skills in Python and SQL
• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields, or related work experience

Benefits & Perks

• Comprehensive health plans (including Medical, Dental and Vision insurance for full-time employees)
• Unlimited PTO
• Competitive salary packages
• Life insurance
• Disability benefits
• Supplemental Optional Life Insurance Benefits
• FSA Options Optional
• HSA with Company Match
• 401k program with Company Match
• Fertility Assistance and Planning options
• Wellhub & ClassPass fitness platforms
• Comprehensive Pet Insurance options
• Financial Wellbeing & Student Loan Program access
• Access to additional Mental Health & Wellbeing resources
• Pre-tax Commuter/Transit Benefits
• Free Rocket Lawyer account with online access to an extensive legal documents library and brilliant licensed attorneys at discounted rates 

Interview Process:

• Recruiter Phone Screen
• Role Assessment(s)
• Hiring Manager Interview
• Panel Interviews
• Final Interview

Role Description:

Our technology hinges on flawless execution of rendezvous, proximity operations and docking (RPOD) and stands at the intersection of Space Domain Awareness (SDA), robotics, and in-space upgrades. Complex algorithms are essential to unlocking this vision. This is the domain of GNC Engineers. You’ll primarily focus on the design, build, test, analysis and in orbit operation of the GNC system central to our rendezvous and proximity operations spacecraft and Space Domain Awareness (SDA) products.

If you have a background expertise in a relevant domain such as orbital mechanics, optimal control, spacecraft systems design, sensor fusion and navigation, and/or software development and you’re excited about making a big impact while leaning into collaboration—surrounded by Flagstaff’s Ponderosa pines or the Denver Rockies—we’d love to hear from you!

Key Responsibilities:

Architecture and Investigation

• Architect solutions necessary to accomplish space mission objectives around space domain awareness and RPOD with an emphasis on autonomy, from both a hardware and software perspective.
• Evaluate and select appropriate techniques to achieve mission such as machine learning methods, physics-informed solutions, stochastic methods, Kalman Filters, etc.
• Assist in proposal capture efforts with feasibility analysis and engage with private/public partners, Department of Defense, Other Government Agencies, and other commercial partnerships.

Architecture Design

• Develop architecture, lead trade studies and lead GNC team from conceptualization to flight for RPOD missions
• Design algorithms, simulations, and tools for orbit determination, state estimation, uncertainty propagation to support SDA efforts
• Analyze and source datasets for training and validation or algorithm performance.
• Build and test modeling and simulation tools for orbital/cislunar dynamics, sensor modeling, and visualization.
• Six degree of freedom modeling, simulation and validation of space craft dynamics, sensors and algorithms, including for RPOD missions.

Implementation

• Collaborate with the software and GNC teams to implement algorithm in flight software.
• Heavily support hardware-in-the-loop testing for integrated system validation.
• Design concepts of operations (CONOPS) that balance thermal, power, momentum and communications for spacecraft missions.
• Provide mission operations training and support.

Qualifications:

Required:

• Bachelor’s degree in a technical engineering discipline
• 5+ years of experience working in guidance, navigation, and control
• Software development experience in Python
• Experience developing, debugging, and deploying GNC sensors, effectors and algorithms that have been used in real world applications/projects
• Ability to work in a fast-paced, autonomously driven, and demanding start-up atmosphere
• Proven ability to lead a project from conception to completion

Desired:

• Experience with cradle-to-grave spacecraft design, testing, verification/validation and in-orbit mission operations
• Expertise in either guidance, navigation or control
• Experience with multi-body astrodynamics
• Experience with Git, Linux and Basilisk
• Software development experience in C/C++
• Capable of identifying and solving complex problems with little to no supervision or direction
• Excellent communication skills both written and verbal

Additional Requirements:

Must be willing to work extended hours and weekends as needed.

Compensation and Benefits:  

Your base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience. The anticipated salary range for this role is $180,000 - $280,000 annually. 

Base salary is just one part of your total rewards package at Katalyst. You will also be eligible for long-term incentives, in the form of the Employee Stock Option and Equity Plan, as well as a relocation bonus and other discretionary bonuses. You will also receive access to comprehensive medical, vision, and dental coverage, and unlimited Paid Time Off.

At Katalyst our work on projects involving the U.S. Department of Defense requires adherence to International Traffic in Arms Regulations (ITAR), 22 C.F.R. Parts 120-130, which requires compliance with U.S. export laws before allowing employees to perform certain positions. Currently, our available roles necessitate access to ITAR-controlled information, and as a result, Katalyst would have to ensure any non-US person is authorized access to ITAR information before the commencement of employment. We are committed to equal employment opportunities and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Spire is making a fundamental shift in how it operates its constellation. We are moving from a model where trained operators watch dashboards and escalate to experts, to one where the system is fully autonomous, self-healing, and data intelligent. This Director will lead that transformation. You will set the technical vision, define the architecture, build and inspire the team, and personally raise the standard for what modern space operations look like. 

The old model relies on operators, escalations, manual processes, and institutional knowledge locked in the heads of a few experts. It does not scale and it does not belong in a modern space company. We know what we want to replace it with: SRE principles applied to a constellation, autonomous fault handling, AI-driven anomaly detection, low toil, high data quality, and continuous improvement baked into the system. 

What This Role Is Not: 

This is not a role for someone who wants to graduate out of technical work. If your ideal week is back-to-back 1:1s, sprint ceremonies, and stakeholder syncs, this is not the right fit. We need a director who writes code, reviews architecture, challenges technical decisions, and earns the team's respect through demonstrated craft and not just tenure or title. 

What You Will Work On: 

Technical Leadership 

• Define and own the technical roadmap for autonomous constellation operations
• Set the architectural direction for the data platform, reliability systems, and automation infrastructure
• Stay hands-on: review code, prototype solutions, and get into the details when it matters
• Establish engineering standards across code quality, system design, testing, and observability, and hold the team to them
• Be the person engineers come to when the problem is genuinely hard

Team Building & Culture 

• Recruit, develop, and retain a team of 6 to 10 world-class reliability and platform engineers
• Set the pace, tone, and ambition for the team and make being on it feel like a privilege
• Create an environment where engineers grow fast, own their work, and ship things they are proud of
• Identify gaps and level up engineers through mentorship and not just management

Operational Transformation 

• Lead the shift from manual, operator-driven processes to fully automated and self-healing operations
• Define and drive toward SLOs, error budgets, and reliability targets for the constellation
• Partner with satellite operations and mission teams to translate pain into software solutions

Cross-Functional Influence 

• Be the technical voice of the team in company-wide conversations about architecture, infrastructure, and platform strategy
• Influence how Spire thinks about automation, data, and AI/ML across the broader engineering organization

Basic Qualifications: 

• 7+ years of software engineering experience, with at least 3 in a technical leadership or staff-level individual contributor role
• Demonstrated track record building and shipping reliable production systems at scale. You have owned things that could not go down.
• Deep technical credibility. Engineers on your teams have respected your judgment and not just your title.
• Experience with SRE principles, reliability engineering, or large-scale automation. You have reduced toil systematically and not just complained about it.
• Strong foundation in Python, distributed systems, data platforms, and cloud infrastructure
• Experience hiring and developing engineers. You know what great looks like and how to find it.
• The communication and influence skills to drive technical decisions across teams you do not directly control

Preferred Qualifications: 

• Experience applying AI/ML or advanced analytics to operational or monitoring problems
• Experience writing performance software in Rust
• Background in space systems, aerospace, or highly constrained real-time environments
• Experience building data lakes, telemetry platforms, or observability infrastructure at scale
• A history of leading teams through technical transformations and not just maintaining the status quo

Spire operates a hybrid work model, and this position will require you to work a minimum of three days per week in the office.

Access to US export-controlled software and/or technology may be required for this role. If needed, Spire will arrange the necessary licenses—this is not something candidates need to have before applying. _#LI-MK1

About the Opportunity

We're seeking a Senior Software Engineer to drive key technical initiatives across our computational imaging pipeline. In this high-impact role, you'll own the complex systems responsible for deploying, scaling, and monitoring our regulated AI algorithms end-to-end. You will influence the architecture of our system, ensuring our solutions meet medical standards for quality and performance, while mentoring other engineers and helping shape our technical culture.

About the Team

You will join our expert Computational Imaging team, where we develop sophisticated algorithms to enhance and improve medical imaging. We are focused on improving the quality and clinical value of medical images, creating powerful, extra software components that correct artifacts, standardize data, and ensure the utmost precision before the final analysis. Our work is essential for elevating the reliability and accuracy of Cleerly’s regulated products.

Responsibilities

• Design, build, and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms.
• Design extensible system architectures and make pragmatic trade-offs that balance performance, security, and maintainability.
• Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability.
• Ensure high availability and observability of our services; improve alerting, logging, and incident response across the stack.
• Set and uphold strong engineering standards via code reviews, technical mentorship, and design documentation.
• Lead technical design reviews and system decomposition efforts across teams.
• Proactively identify risks and gaps in operational or architectural resilience, and drive durable improvements.
• Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation.
• Design and implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards 
• Contribute to the necessary technical documentation required for regulatory submissions.

Requirements 

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field (or equivalent experience).
• 8–12 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).
• Demonstrable capability in designing, implementing, and securing RESTful web services
• Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes).
• Experience with AWS, GitHub, and continuous integration pipelines
• Proven track record of architecting and delivering scalable systems in production environments.
• Experience mentoring engineers and raising the technical bar through reviews and design feedback.
• Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability.
• Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks).
• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders.

Preferred:

• Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements.
• Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $153,000 - $179,000
• TTC: $176,000 - $206,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

Position Overview:

We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova’s agentic experiences. This role focuses on applied Machine Learning in production environments: retrieval systems, evaluation frameworks, and model integration layers that make AI features reliable, scalable, and repeatable. You will design and implement the underlying components that support rich, intelligent interactions in the Iterable platform.

You will work closely with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company. The work blends hands-on engineering with system design, and is ideal for someone who can drive complex efforts independently, make practical architectural decisions, and collaborate in a fast-moving, cross-functional product environment.

Responsibilities:

• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers.
• Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring.
• Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently.
• Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics.
• Prototype applied ML solutions to validate feasibility before investing in full builds.
• Ensure secure, robust handling of data used in ML workflows and retrieval operations.
• Collaborate with product, design, and engineering to align ML system design with user experience and product goals.
• Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript.

Qualifications:

• 5+ years experience as a Machine Learning Engineer or similar role focused on production systems.
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Prior work integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity.
• Strong communication and collaboration skills in a distributed environment.

Bonus Points

• Experience building ML or LLM platforms, tooling, or developer-facing frameworks.
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures.
• Familiarity with event-driven systems or streaming architectures.
• Experience with model observability, performance monitoring, or proactive regression detection.
• Background in personalization, recommendations, or applied NLP.
• Experience working in remote-first engineering teams.

Perks & Benefits:

• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer’s needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

• Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
• Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
• Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

We are seeking an experienced Staff Observability Consultant with deep expertise in OpenTelemetry and strong Platform Engineering capabilities to help organizations implement, optimize, and scale their observability infrastructure. This role requires a seasoned consultant who can design comprehensive telemetry strategies, implement distributed tracing solutions, establish robust monitoring practices, and interface closely with clients on the observability journey.

Key Responsibilities:

OpenTelemetry & Observability

• Design and implement end-to-end OpenTelemetry solutions across diverse technology stacks
• Configure and deploy OpenTelemetry Collectors for efficient data collection, processing, sampling, and routing
• Establish telemetry pipelines for metrics, traces, and logs across microservices architectures
• Optimize collector configurations for performance, reliability, and cost-effectiveness

Platform Engineering & Infrastructure

• Augment existing infrastructure with with integrated observability solutions
• Implement Infrastructure as Code (IaC) solutions using Terraform, Pulumi, CloudFormation, etc.
• Architect and manage Kubernetes clusters with comprehensive monitoring and logging
• Build CI/CD pipelines with embedded observability and automated testing

Site Reliability Engineering (SRE)

• Establish and maintain Service Level Indicators (SLIs), Objectives (SLOs), and Agreements (SLAs)
• Implement error budgets, toil reduction strategies, and capacity planning
• Support incident response procedures and post-mortem processes

Cloud & DevOps Engineering

• Deploy and manage observability infrastructure across AWS, GCP, and Azure
• Establish security, compliance, and governance frameworks for telemetry data
• Experience automating Agent Evaluations in CI/CD pipelines and observability backends.

Required Qualifications:

Core Observability & OpenTelemetry

• 3-7 years of experience in observability, monitoring, and distributed systems
• Deep hands-on experience with OpenTelemetry ecosystem, including SDKs, APIs, and specifications
• Proficiency with OpenTelemetry Collector configuration, processors, exporters, and receivers
• Strong understanding of telemetry data models, semantic conventions, and instrumentation best practices

Platform Engineering & DevOps

• 5+ years of Platform Engineering or DevOps experience with focus on site reliability, observability, and incident response
• Proficiency with Infrastructure as Code tools (Terraform, Pulumi, CloudFormation, CDK)
• Strong experience with CI/CD platforms (GitHub Actions, GitLab CI, Jenkins, ArgoCD)

Cloud & Infrastructure

• Hands-on experience with major cloud providers (AWS, GCP, Azure) and their observability services
• Experience with container technologies (Docker, Podman) and container registries
• Knowledge of networking, security, load balancing, and distributed systems concepts

Site Reliability Engineering

• Experience implementing SRE practices including error budgets and toil metrics
• Proficiency in incident management, on-call procedures, and post-mortem culture
• Experience with capacity planning, performance optimization, and scalability design

Programming & Automation

• Proficiency in multiple programming languages preferred (Go, Python, Java, Node.js, Rust)
• Strong scripting and automation skills (Bash, Python, PowerShell)
• Understanding of software engineering best practices and testing methodologies

Preferred Qualifications (Exceptional Candidates)

AI & Agentic Frameworks

• Understanding of Large Language Models (LLMs) and their application in DevOps
• Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG)
• Experience with AI/ML model deployment and monitoring in production environments

Leadership & Communication

• Strong technical writing and documentation skills
• Ability to present complex technical concepts to diverse stakeholders
• A passion for knowledge sharing

Key Competencies

• Systems thinking and ability to design holistic observability solutions
• Strong analytical and troubleshooting skills for complex distributed systems
• Curiosity about emerging technologies, particularly AI applications in operations
• Adaptability to rapidly evolving cloud-native and observability technologies
• Collaborative mindset with focus on enabling developer productivity and system reliability

What Sets Exceptional Candidates Apart:

• Experience with Honeycomb
• Contributions to open-source observability or AI framework projects
• Track record of implementing platform engineering solutions that significantly improved developer experience
• Experience scaling observability infrastructure to handle high event volume

What to know before you apply: 

• This role will require being in the Denver office three days per week and up to 20% travel within the United States.
• Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
• The Denver base salary range for this role is $160,000 - $200,000.