Remote, Remote, United States About the Role We're hiring a Junior Full-Stack Developer to help us build technology that matters. At the Patrick J. McGovern Foundation, we believe that data and AI products can be catalysts for systemic change when built with rigor, deployed with intention, and designed alongside the people they're meant to serve. Our Products & Services team operates like a technical studio inside a foundation. Small team. High trust. Rapid cycles. We're looking for a Junior Full-Stack Developer to join us in building cloud-based tools that translate machine learning insights into actionable applications for the social sector. As a Junior Full-Stack Developer, you'll contribute across the entire development lifecycle—from cloud architecture and backend services to user-facing applications. You'll grow through doing: taking on increasing ownership, learning from experienced engineers, and shipping products that support real-world impact. If you're looking for a place to grow your craft while contributing to meaningful work, we want to hear from you. This is an early-career, growth-oriented engineering role for developers with a strong technical foundation and ready to deepen their experience building production systems in a mission-driven environment. Junior Full-Stack Developers progressively take on greater ownership over time, developing full-stack capabilities through mentorship, hands-on contribution, and exposure to end-to-end systems while learning how to balance technical quality, user needs, and impact. How you’ll make an impact: Collaborative Development: Work closely with the Director, Data Scientist, Full-Stack Developer, and Platform Engineer to understand project requirements and contribute to the development of AI-based products. Contribute to the vision and execution of product architecture, UI/UX designs, infrastructure deployment, and ensuring high-quality work output. Nonprofit Consultation Support: Contribute to consultations with nonprofit partners exploring data and technology solutions. The ability to explain technical concepts with empathy and clarity is critical, as this role helps equip partners with the tools and knowledge to succeed. Product Integration: Contribute to the design, development, and deployment of full-stack applications for cloud-based solutions that align with the rapid prototyping development approach, under the guidance of senior team members, with increasing ownership over time. Collaborate with the team to integrate ML model predictions into user-friendly interfaces, ensuring the reliability, safety, and scalability of the end products. User-Centric Design: Implement intuitive user interface s for AI-backed web and mobile applications. Understand end-user needs and requirements to design and develop applications that effectively address challenges within the social good sector. Prototype, test, and iterate on full-stack solutions, incorporating user feedback for continuous improvement. Cross-Functional Collaboration: Collaborate with team members to address communication, outreach, and resource needs related to front-end and mobile development. Ensure effective communication with cross-functional teams, contributing to the success of AI products. Learning & Growth: Seek and incorporate feedback through code reviews and pair programming. Grow familiarity with cloud infrastructure, deployment workflows, and system design. Build confidence working across the full stack over time, with mentorship and support. What We Offer Health Coverage – Foundation-paid medical, dental, and vision insurance for employees, spouses/domestic partners, and dependents. HSA/FSA plans, life insurance, and short- and long-term disability coverage. Long-term Rewards – 401(k) retirement plan with generous matching up to 6% of annual pay, plus an additional discretionary match at the end of the year. Flexible PTO – Progressive approach to PTO reflecting our respect for diversity, commitment to our team members, and ability to adapt to changing employee values. In addition, the Foundation recognizes 11 paid national holidays per year and may also announce closure for local, regional, or state holidays. Remote Work Environment – Ability to work 100% remotely, but not alone - with mature, socially minded professionals. Wellness Support – In addition to our health coverage, we offer access to Ginger+, an Active and Fit Gym membership discount, and Smart Spend Plus, along with financial well-being providers. Parental Leave – Up to 6 months of gender-neutral paid leave for parents and caregivers when they have a new addition to their families. Learning Reimbursements – Foundation policy encouraging employees to explore development opportunities such as peer learning, internal trainings, and external activities; savings on student loans (available via insurance provider). Philanthropic Gift Matching – opportunity for team members to support vulnerable communities, reflecting PJMF’s commitment to social impact. $70,000 - $106,000 a year Salary Philosophy PJMF is committed to fair and transparent compensation practices. Our salary ranges are informed by market data from peer organizations in our sector. Our salaries are competitive and equitable and align with peers in the same job group. Because salary ranges are small and the internal parity review is thorough, offers are firm. Starting salaries are typically placed in the lower half of the range. Final offers are determined by the scope of the position, the candidate's relevant experience, and internal equity. It is important to us that our hiring process is accessible to everyone. If you require accommodations to participate in the interview process, please let us know when you apply. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. What you will need to succeed: Experience – 1-3 years of professional experience in full-stack development, with proven expertise in both UI development and backend integration. Experience with Python-based codebases is required. Development – Proficiency in JavaScript, HTML, CSS, and experience with modern front-end frameworks such as React or React Native. Strong programming experience with Python or Go is strongly preferred. Experience with CI/CD tools (e.g., GitHub Actions, etc), source control (GitHub), and issue tracking (Jira) is also strongly preferred. Infrastructure – Familiarity with relational databases (e.g., PostgreSQL, MySQL) is required, and familiarity with NoSQL systems (e.g., MongoDB, DynamoDB) is a plus. Experience with cloud services (e.g. AWS), containerization (e.g., Docker), orchestration (e.g., Kubernetes), and Infrastructure as Code (e.g., Terraform) is also a plus, but not required. Communication – Excellent communication skills, both written and verbal, to convey technical concepts to diverse audiences. Teamwork – Effective team player who understands the responsibility every individual brings to the table and how to encourage and drive results from each team member; ability to work collaboratively within a high-performance, startup-like environment. High Performance – Ability to quickly learn new technologies and methodologies to ensure successful and timely completion of product development. Results-oriented – Highly organized and detail-oriented, self-driven, and able to adapt to learning and implementing new technologies, and creative in solving issues as they arise. Cultural alignment – An advocate for social progress; interest in emerging technologies and their ability to advance societal outcomes. Work eligibility – Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Toronto, ON, Canada About Fulfil Fulfil is the modern ERP for commerce. Built to power the fastest-growing eCommerce brands, our platform brings together order management, inventory, accounting, and more, turning complex operations into a strategic advantage. We’re trusted by brands like HexClad, Ridge Wallet, Caraway, and Resident, and backed by people who want to change the way merchant operations are run. We believe in deep work, radical accountability, and building tools that let sharp people move faster. About the Role As a Python Engineer (Full Stack & AI) at Fulfil, you will design and build next-generation systems that power millions of customer orders and financial transactions for some of the world’s fastest-growing merchants. Our Python-based platform operates at a significant scale, handling millions of transactions per hour. Your work will have a direct impact on system reliability, scalability, and product innovation. You’ll collaborate closely with teammates across Canada, the U.S., and India, working in a highly ownership-driven environment that values clean architecture, pragmatic engineering, and thoughtful problem-solving. Location: Toronto, Ontario (in-office 5 days per week) Type: Full-Time Expected Start Date: Immediately What You’ll Do Own the Full Stack Design, build, and maintain end-to-end functionality across our Python-based platform, from backend services to frontend integrations. Work within a large, mature codebase while contributing to its long-term evolution and scalability. Deliver Features at Speed Lead the design, development, testing, and deployment of new features that directly support high-growth merchants. Balance rapid delivery with long-term maintainability. Apply AI in Production Integrate AI-powered capabilities into Fulfil’s ERP using LLMs (e.g., OpenAI, Anthropic). Build intelligent workflows that enhance automation, decision-making, and merchant experience across orders, financials, and operations. Scale with Confidence Design and optimize REST and GraphQL APIs (600+ endpoints), microservices, and background processing pipelines. Work with containerized infrastructure (Docker/Kubernetes) to support high availability and zero-downtime deployments. Champion Code Quality Refactor and modernize legacy systems. Write well-tested, readable code using pytest. Participate in code reviews and architectural discussions to raise the bar across the team. Build Ecosystem Integrations Develop and maintain integrations with major commerce platforms (Shopify, Amazon) and logistics providers (FedEx, DHL). Ensure reliable data flows across external systems and Fulfil’s core platform. Required Experience 5+ years of experience, ideally, building applications at scale from scratch. Strong experience building large-scale backend systems and microservices using Python. Hands-on experience with ORMs (e.g., SQLAlchemy, Django ORM) and relational databases (PostgreSQL preferred). Proficiency with distributed systems components such as Celery, Redis, RabbitMQ, and background processing. Experience writing automated tests (pytest) and using Git in a collaborative environment. Demonstrated ownership—seeing projects through from design to production and ongoing support. Bonus Points Experience scaling systems at a high-growth tech company. Familiarity with cloud platforms (Google Cloud, Heroku, etc.). Passion for optimizing distributed systems or e-commerce workflows. Domain-Focused Product Engineering: Experience building or scaling production software in commerce, logistics, or operations domains (e.g., order management, inventory, fulfillment, WMS) or in FinTech/financial systems (payments, reconciliation, revenue recognition, invoicing).

Houston, TX, USA OVERVIEW I seek a highly qualified Python research software consultant to assist in refactoring, organizing, and documenting two related social science research codebases for publication-grade reproducibility and open-source public release. This is a short-term, remote consulting opportunity with competitive compensation. PROJECTS This work comprises two related components: PNAS Research Article Codebase Prepare for publication the Python hierarchical Bayesian modeling (HBM) codebase underlying a manuscript soon to be submitted to PNAS on global scientific production. This codebase requires refactoring, reorganization, and documentation to meet publication-grade standards of clarity, structure, and computational reproducibility. Advanced Data Analytics Platform Codebase Prepare for public release version 2.0 of an advanced data analytics platform built with Python, SQLAlchemy, and PostgreSQL as an open-source demonstration platform for research on the contemporary history of quantum information science (QIS). This role focuses on research software engineering, code organization, documentation, and reproducibility rather than on statistical model development. RESPONSIBILITIES Improve the clarity, structure, reproducibility, and maintainability of both codebases. Develop clear documentation, including README files, docstrings, in-code comments, and usage examples. Ensure reliable, reproducible execution from raw data to final analytical outputs. SCOPE The two codebases together include approximately 20 Jupyter notebooks, some as long as 3,000 lines. The consultant will focus on the highest-priority components necessary to produce a clean, reproducible, publication-ready codebase rather than refactoring every notebook in full. QUALIFICATIONS Ph.D., advanced graduate student, or experienced research software engineer in computer science, software engineering, data science, or a related field. Strong expertise in Python. Experience refactoring, organizing, and documenting research codebases. Experience preparing computational research code for peer-reviewed publication and computational reproducibility, especially code supporting a major article submission in computational social science or related fields, preferred. Experience with hierarchical Bayesian modeling preferred. Experience preparing codebases for open-source public release preferred. Experience with reproducible research practices, including environment management, workflows, and version control, preferred. Experience with SQLAlchemy preferred. ADDITIONAL INFORMATION Compensation: Competitive hourly compensation of $80–$150, with total compensation in the range of $7,000–$10,000, depending on qualifications, experience, and scope of work. Duration: Flexible, with total hours depending on consultant availability, qualifications, and final scope. All work must be completed by June 30, 2026. Location: Remote. HOW TO APPLY Please send a brief statement of interest outlining your background and relevant experience, together with your CV and links to any code samples or repositories, to: Professor Roger Hart, Department of History & Geography, Texas Southern University Roger.Hart@TSU.edu http://rhart.org/

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