Remote, United States About Nava Nava is a consultancy and public benefit corporation working to make government services simple and effective. Since 2015, federal, state, and local agencies have trusted Nava to help solve highly scrutinized technology modernization challenges. As a client services company, we guide agencies constrained by legacy systems to a future with sharp user experiences built on secure, reliable, fault-tolerant cloud infrastructure. We bill for our time, offering our expertise and problem-solving approach to help our government partners enhance their digital products and services. People are at the heart of our work, from members of the public who rely on benefit programs to government agency staff. Through human-centered design and modern engineering best practices, we help our government partners understand user needs and deliver on their missions more effectively. This focus gives everyone at Nava the opportunity to do work that is meaningful, impactful, and deeply connected to public good. Position summary In this role, you’ll partner with government stakeholders and Nava’s engineering, design, and product teams to modernize data architectures and pipelines for critical public programs. You’ll design and implement scalable data models and databases, improve pipeline performance and security, and build systems that support the storage, processing, and analysis of large-scale data. You will support the data needs of multiple teams, systems, and products in addition to creating and optimizing our government partners' data architecture. What you'll do Work with cross-functional project teams to gather business requirements and translate to detailed technical specifications Work with Government partners to assist and develop data engineering applications and pipelines that will enable data services and processing capabilities, such as advanced analytics, AI/ML, and experimentation Design, develop, test, automate, and deploy data engineering solutions in a cloud platforms, such as AWS Participate in software design and code reviews Develop automated testing, monitoring and alerting, and CI/CD for production systems Required skills Minimum of 8 years of experience with professional software engineering practices using such tools and methodologies as Agile Software Development, Test Driven Development, CI/CD, and Source Code Management Experience with building ETL pipelines to ingest, process, and store data Prior experience with Python programming for both data processing and server-side use cases Experience with data cleaning, modeling, schema design while protecting sensitive data Proficient with building data integrations using both API and file-based protocols Proficient with relational databases and advanced SQL queries, particularly with Postgresql Experience with using data observability tools to maintain data infrastructure and data quality Proficient in refining high-level goals into high-impact, low-effort tasks and milestones based on human-centered design practices to prioritize options for stakeholders Desired skills Experience using data observability tools to maintain data infrastructure and data quality Experience with AWS services like ECS, S3, CloudWatch, and Glue Infrastructure as code experience tools like Terraform Legacy modernization, especially with mainframes Comfortable troubleshooting complex data and systems interaction problems Please note: the level of the role will be determined by Nava leadership based on experience and skillset. Compensation $120,600 - $135,900 USD

Long Beach, Hybrid, California, USA Rebel Space Technologies is seeking a talented and experienced Machine Learning Engineer to join our team. Machine Learning Engineer: At Rebel Space, our mission is to protect critical space infrastructure through enhanced observability and space system cybersecurity. We believe that as space infrastructure expands, it will be increasingly difficult to secure and monitor these systems against critical failures or evolving cyber threats. To address this, we are building software that empowers developers and operators to rigorously evaluate and secure their systems from conception through to operations. Our technology supercharges space infrastructure, ensuring resilience against evolving threats in an increasingly complex environment. We’re looking for a talented Machine Learning Engineer to join us in pioneering the next generation of space system security. As a Machine Learning Engineer at Rebel Space, you’ll design, implement, and optimize ML models for anomaly detection in satellite communications. You’ll help architect secure, scalable infrastructure for ML workloads within demanding government and defense compliance environments. This position is ideal for someone who thrives in dynamic, fast-paced R&D environments, is comfortable building systems from the ground up, and has a bias toward elegant, performant, and reliable code. Responsibilities: Develop and maintain machine learning infrastructure that is portable and flexible, supporting deployments both in cloud environments and on edge devices Research, prototype, and survey different ML architecture and workflow optimization techniques Design and implement proof-of-concept custom optimizations, then demonstrate how these optimizations improve the performance of existing machine learning models when applied to actual real-world datasets. Build data collections, labeling pipelines, and evaluation pipelines. Research and develop machine learning models for physical sensor systems. Extend existing ML libraries and frameworks. Create and deliver reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews. Own technical projects from start to finish and be responsible for major technical decisions and tradeoffs. Effectively participate in team planning, code reviews, and design discussions. Basic Qualifications: Bachelor's degree in Computer Science, Electrical Engineer, Physics or related technical discipline. 3+ years of relevant industry experience in data analytics and machine learning Strong expertise in scientific Python (NumPy, SciPy, Pandas) and modern ML frameworks (PyTorch, TensorFlow, JAX, Scikit-Learn, Keras) Proficiency in SQL and experience with relational or time-series databases Proven experience applying statistical modeling, data analysis, and inference to extract actionable insights from large and complex datasets Familiarity with overall big data analysis, system backend integration with new ML systems, and large-scale data processing Proficiency in data visualization tools (e.g., Matplotlib, Seaborn, Power BI) to effectively communicate findings Excellent understanding of algorithms, data structures, and coding standards Strong communication and behavioral skills Motivated self-starter that can work autonomously and as part of a team Preferred Qualifications: PhD, Masters, or equivalent in Computer Science, Electrical Engineer, Physics or related field with 5+ years of professional experience in machine learning engineering Knowledge of experiment tracking, model deployment strategies, data versioning, and monitoring Experience with ML infrastructure tools (e.g. MLflow, Kubeflow, Airflow, feature stores, model registries) Prior experience with real-time data processing, prediction systems, or active learning pipelines Exposure to synthetic data generation techniques (GANs, simulation platforms). Experience designing reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews Experience at early-stage startups and remote-first organizations Passionate about building autonomous systems Benefits: Premium Healthcare Benefits: We offer comprehensive medical, dental, and vision plans at little to no cost to you. Stock Options: Own meaningful equity in Rebel Space. Generous PTO: Includes flexible vacation and company paid holidays. Maternity/paternity leave. Flexible hybrid work options. Opportunity to shape the future of space cybersecurity and observability! The estimated salary range for this role is $140,000-$220,000 + equity in the company, inclusive of all levels/seniority within this discipline. As a growing company, the salary range is intentionally wide as we determine the most appropriate package for each individual taking into consideration years of experience, location, educational background, and unique skills and abilities as demonstrated throughout the interview process. ITAR Requirements: To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), applicants must be a US citizen, lawful permanent resident of the U.S., protected individual as defined by 8 USC 1324b(a)(3), or eligible to obtain the required authorization from the US Department of State. Learn more about the ITAR here. Rebel Space Technologies is an equal-opportunity employer, and we encourage candidates from all backgrounds to apply. If you are someone passionate to work on problems that matter, we’d love to hear from you. Basic Qualifications: US Citizen Bachelor's degree in Computer Science, Electrical Engineer, Physics or related technical discipline. 3+ years of relevant industry experience in data analytics and machine learning Strong expertise in scientific Python (NumPy, SciPy, Pandas) and modern ML frameworks (PyTorch, TensorFlow, JAX, Scikit-Learn, Keras) Proficiency in SQL and experience with relational or time-series databases Proven experience applying statistical modeling, data analysis, and inference to extract actionable insights from large and complex datasets Familiarity with overall big data analysis, system backend integration with new ML systems, and large-scale data processing Proficiency in data visualization tools (e.g., Matplotlib, Seaborn, Power BI) to effectively communicate findings Excellent understanding of algorithms, data structures, and coding standards Strong communication and behavioral skills Motivated self-starter that can work autonomously and as part of a team Preferred Qualifications: PhD, Masters, or equivalent in Computer Science, Electrical Engineer, Physics or related field with 5+ years of professional experience in machine learning engineering Knowledge of experiment tracking, model deployment strategies, data versioning, and monitoring Experience with ML infrastructure tools (e.g. MLflow, Kubeflow, Airflow, feature stores, model registries) Prior experience with real-time data processing, prediction systems, or active learning pipelines Exposure to synthetic data generation techniques (GANs, simulation platforms). Experience designing reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews Experience at early-stage startups and remote-first organizations Passionate about building autonomous systems

Oakland, CA, United States Hi! I work on product & engineering at Redivis, and we're hiring a Research Advocate and Support Engineer to join our team. We're a data platform for academic research at leading U.S. institutions, and we're looking for someone to take ownership of building and supporting our growing community of researchers and data administrators. We’re looking for an empathetic, clear communicator who is proficient in Python, R, and/or SQL, and loves to write, present, and debug data pipelines. Apply here: https://redivis.homerun.co/technical-evangelist-and-support-engineer/en Company: https://redivis.com Location: Remote (United States) Salary: $140K + equity + benefits Strong technical proficiency in using Python, R, and/or SQL for data science. Solid understanding of data science principles, methodologies, and common tools. User empathy around the challenges and pain points when working with research data. Experience creating and maintaining teaching or support materials. Excellent written and verbal communication skills, with the ability to explain complex technical concepts clearly and concisely. Comfortable adapting to the needs of a highly diverse user base spanning numerous scientific disciplines and varying levels of data science expertise. Strong problem-solving skills and a methodical approach to troubleshooting.

Remote, United States Chime Engineering is growing rapidly as we scale to meet the financial needs of our members—and that growth depends on strong, secure, and efficient engineering foundations. We’re hiring a Senior Python Core Engineer- to join the Languages & Frameworks team within Engineering Services, with a mission to standardize and strengthen Chime’s Python ecosystem. Python is increasingly foundational to our data engineering, analytics, machine learning, and emerging AI initiatives. As Python adoption expands, we need clear ownership and stewardship over Python releases, packaging, base images, and shared libraries to reduce security risk, eliminate duplicated effort, add guardrails against AI generated code, and make builds and runtimes more reliable and reproducible. In this role, you’ll be the technical leader for Python foundations across the company responsible for owning the lifecycle of Python versions, defining best practices, improving build and dependency workflows, and maintaining key internal Python libraries. You’ll partner closely with platform teams, CI/CD stakeholders and data/ML orgs to drive improvements that make Python development faster, safer, and more scalable. The base salary offered for this role and level of experience will begin at $187,000 and up to $259,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. In this role, you can expect to: *Own Chime’s Python version standards, upgrade cadence, and compliance, reducing EOL exposure and security patch lag *Design and drive safe, repeatable Python upgrade processes across services and shared libraries, enabling teams to adopt new versions with minimal friction *Establish clear dependency management practices (e.g., version locking policies, upgrade safety, library compatibility strategies) *Partner with CI/CD stakeholders to improve build performance, reliability, and developer experience for Python projects *Maintain and develop critical internal Python libraries including roadmap, quality, and adoption *Define and evangelize Python best practices (“the Chime way”), aligned with community standards, and support teams through documentation and enablement *Identify and drive opportunities to maximize returns from the Python + AI ecosystem, evaluating tools, practices, and vendor options that improve iteration speed and outcomes To Thrive in this Role, You Have: *5+ years of software engineering experience, with deep hands-on expertise in Python in production *Strong experience with Python build tooling, and an understanding of tradeoffs in versioning and distribution *Understanding of asynchronous and synchronous data-sharing patterns (pub/sub, RPC, caching, etc.). *Solid knowledge of containerized environments and build systems (Docker images, CI pipelines, caching, reproducible builds) *Experience building and maintaining shared libraries used by multiple teams, including API design, backwards compatibility, and release management *A security- and reliability-first mindset, especially around EOL management, patching and build integrity *Strong cross-functional collaboration skills—able to influence without authority and align multiple teams around standards and migrations *Comfort operating with ambiguous requirements, creating clarity through docs, prototypes, and incremental rollout plans *Bonus: experience working in/supporting data engineering and ML *Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.

Warsaw (fully remote), Poland Senior Python Backend Engineer We’re looking for Python backend engineers to work on a trustless supercluster of performance-proofed GPU-enabled sandboxed docker container runners controlled by truly decentralized algorithms (not just PAXOS or RAFT). Wow, that was a mouthful... If you found it interesting, join Reef Technologies and tackle complex technical challenges like this on your own terms: Contribute from wherever you like—we are fully remote but like to stay in sync, so we’re currently hiring in EMEA/APAC. Set your own time commitment, as long as it’s at least 30h per week See how we work in our handbook Influence the way we operate through our Sociocracy 3.0 decision-making process Salary on a B2B contract: 45-70 USD or 180-280 PLN per hour Flexible work schedule (as measured with a time tracker) We automatically adjust rates based on inflation twice a year So, what do you think? You don't even need a CV, just click here and shoot a few quick commands to apply. We're looking for someone with 5+ years of programming experience, including at least a year with Python (including opensource and significant personal projects).

Toronto, Ontario, Canada Deloitte is seeking an experienced GenAI & Python Specialist to join our dynamic Operate team on a 1‑year fixed term employment basis. In this role, you will design, build, and scale Generative AI solutions using Python‑based frameworks, Large Language Models (LLMs), and advanced retrieval‑augmented generation (RAG) techniques. What will your typical day look like? -Strong Python development for GenAI and agentic systems Design and implementation of Agentic AI workflows using LangChain, LangGraph, ADK, MCP Development and orchestration of multi‑agent systems Implementation of Retrieval‑Augmented Generation (RAG), including advanced RAG techniques Integration and management of vector databases for RAG workflows Design and implementation of memory systems (short‑term, long‑term, persistence, conversational checkpoints) Agentic AI design and orchestration across workflows Work with AI/GenAI models including Gemini and Claude 4.5 on Vertex AI Development of business co‑pilots, including co‑pilot solutions for Risk Analysts Support for business process optimization using GenAI Use of NLU as an add‑on capability where requiredContribution to CTO‑led tools, including: Agent Flow for observability, drift monitoring, feedback loops ML Flow for model evaluation and drift detection Sourcing test results management, including truth tables and evaluations Bringing Agent Flow into existing projects Domain‑specific GenAI solutions for DRO (Data and Regulatory Operations): QA validation and KYC document processing Systematic capture and validation of required fields Automated document checking without extraction Record retrieval and comparison (DNC, ANC, SMC) Agentic framework for document management, data analysis, and data engineering Co‑Labs initiatives: Consolidation across MCP endpoints Agent registries consolidation Combining assets into an accessible catalog Python‑based web scraping and utility development Work with existing Python GitHub repositories Integration with case management tools and Appian workflows (NA10) Building agents on top of Appian workflows using ADK You are someone with these skills, experience & qualifications: 6+ years of hands‑on experience designing and implementing AI / GenAI solutions using Python Strong proficiency in Python engineering for data processing, model integration, APIs, and microservices Deep understanding of Generative AI, LLMs, and NLP concepts and architectures Experience building agentic AI workflows using LangGraph, including multi‑step reasoning, tool‑calling, and planner–executor patterns Advanced knowledge of RAG techniques, including hybrid search, vector and multi‑vector retrieval, embeddings, and context optimization Experience designing and deploying APIs and microservices to production environments Familiarity with traditional ML/NLP techniques such as clustering, extraction, and enrichment to complement GenAI solutions Strong communication skills, a collaborative mindset, and a passion for continuous learning and innovation in the GenAI space