Role Description EO Solutions, an aerospace defense contractor specializing in Space Domain Awareness (SDA), Directed Energy (DE), and advanced AI/ML technologies, is seeking an experienced SDA Research Engineer to join our growing team. This position will serve as the team’s subject-matter expert in astrodynamics and satellite tracking—developing the orbit determination, estimation, and tasking algorithms that drive our space surveillance sensor orchestration system and applying modeling and simulation to evaluate system performance and mission effectiveness. This role is positioned alongside the software development team, actively contributing to the codebase alongside developers to ensure research translates directly into reliable, operational capability. Key Responsibilities - Serve as the team’s subject-matter expert in astrodynamics and satellite tracking, performing orbit determination, sensor tasking, and uncertainty characterization for resident space objects. - Develop, validate, and document estimation and filtering algorithms (e.g., Kalman filtering, batch least-squares) for orbit determination and multi-sensor data fusion. - Define tracking, tasking, and observation requirements that inform the space surveillance sensor orchestration system, and develop the algorithms that drive automated sensor tasking and scheduling. - Build and further develop modeling and simulation tools to evaluate system performance against key metrics. - Apply astrodynamics theory to prototype algorithms and reference implementations that the software engineering team integrates into production systems. - Participate in the software development cycle by attending stand-ups, managing code through Git, and actively developing technical portions of the codebase through bug fixes, performance analysis, and simulation validation. - Collaborate with aerospace SMEs and software engineers to verify algorithm performance against operational data and mission requirements. Qualifications - Ph.D. in Aerospace/Astronautical Engineering (or a closely related field) preferred, with relevant professional experience; exceptional candidates holding an M.S. with substantial experience will also be considered. - Deep expertise in astrodynamics and orbital mechanics, including orbit determination, propagation, and uncertainty characterization. - Strong background in estimation and filtering techniques, such as Kalman filtering, batch least-squares, and multi-sensor data fusion. - Proficiency in Python for algorithm development, analysis, and prototyping. - Experience working with Git or other version tracking software for tracking issues and documenting software development progress. - U.S. citizenship with the ability to obtain and maintain a U.S. Government security clearance. Desired Experience - Experience with Space Domain Awareness (SDA) or space surveillance systems, sensor tasking, and catalog maintenance. - Modeling and simulation experience supporting sensor tasking and orchestration. - Familiarity with electro-optical and/or radar sensor phenomenology, observation processing, and tracking. - Experience working in a software development environment on production-level code. - Publications or conference contributions in astrodynamics, estimation, or SDA. - Experience transitioning research algorithms into operational software in collaboration with software engineering teams. Work Environment & Culture EO Solutions is a rapidly growing startup defense contractor committed to innovation, collaboration, and mission impact. We value community, partnership, and supporting our employees across all locations—Las Vegas, Huntsville, Hawaii, and remote. Compensation Competitive salary based on experience + full benefits package (health, dental, vision, PTO, holidays, 401(k), and more). Final salary range determined by experience and location. Why Join EO Solutions? - Opportunity to contribute to cutting-edge national security and SDA work. - Highly collaborative, people-centered culture. - Growth-focused environment with room to build, refine, and lead processes. - Meaningful mission supporting aerospace and defense innovation.

Title: Research Associate II – In vivo Electrophysiology & Behavior Location: Seattle United States Job Description: Research Associate II – In vivo Electrophysiology & Behavior The mission of the Allen Institute is to understand the principles that govern life and to advance health. Our creative and multi-dimensional teams focus on answering some of the biggest questions in bioscience. We accelerate foundational research, catalyze bold ideas, develop tools and models, and openly share our science to make a broad, transformational impact on the world. The mission of the Allen Institute for Neural Dynamics is focused on fundamental discoveries in systems neuroscience. We are interested in how the brain builds our understanding of the complex world to guide the flexible behaviors that address our biological needs. The answers will be in terms of defined neuron types and circuits interacting across the whole brain and body. We will develop next-generation methods and theories and employ a team-based approach to discovery neuroscience. Knowledge, data, models, and tools will be widely shared to support the development of therapies for brain disorders. We are seeking a Research Associate to contribute to projects seeking to decipher the neural mechanisms of flexible decision-making in mice. This position will leverage state-of-the-art electrophysiological methods, such as Neuropixels probes, as well as molecular and transgenic tools. The goal is to record simultaneously from many anatomically connected regions while mice are engaged in a variety of cognitive tasks. The ideal candidate will be team-oriented and have extensive experience in electrophysiological techniques. The Research Associate will work alongside a diverse team of Scientists, Technicians, Engineers, and Investigators, and so collaboration and communication skills are key. At the Allen Institute, we believe that science is for everyone – and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly. We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment. We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions. Essential Functions - Perform experiments using in vivo electrophysiology, carefully controlled mouse behavior, and neural manipulations - Collaborate with scientists to develop and evaluate new behavioral tasks and associated methods for data collection, quantification, and analysis - Collaborate internally and externally to analyze physiology and behavior data - Additional tasks may include histology and/or surgery - Participate in weekly lab meetings - Train team members to perform procedures *Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.* Required Education and Experience - Bachelor's degree in Neuroscience, Biology, or related discipline - 2 years of relevant experience Preferred Education and Experience - 3 years of experience with in vivo electrophysiology in rodent models - Surgical experience in rodents - Rodent handling and training experience - Ability to write reusable code in Python or Matlab Work Environment - May enter laboratory environment, including potential exposure to lasers, biohazards - Exposure to and handling of laboratory animals required Animal Care Services - Daily exposure to and handling of laboratory animals required - Pre and post-operative care for mice - Administration of compounds to mice (iv, ip, sc, po, im, ro, icv) - Perform health assessments of mice - Perform euthanasia and tissue collections - Perform daily vivarium maintenance and/or closing procedures Physical Demands - Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with lab equipment - Stooping, bending, crouching - Reaching, or climbing ladders Position Type/Expected Hours of Work - This role is currently working onsite and is expected to work onsite for the majority of working hours. The primary work location for this role is 615 Westlake Ave N., with the flexibility to work remotely on a limited basis. Additional Eligibility Qualifications - All employees who work with live animals must complete an Occupational Health medical history form and/or consultation with an Occupational Health Provider and receive clearance to work with animals. Depending on your health history and job responsibilities, an annual respiratory health screening and clearance to use a respirator may also be required. Additional Comments - Please note, this opportunity does not offer work visa sponsorship Annualized Salary Range - $66,500 - $81,350 Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable. Benefits - Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute’s Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute’s 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.

Role Description Innodata is expanding its team of technical experts in LLM training, post-training, and evaluation systems. As an AI/ML Research Engineer, LLM Training & Evaluation, you will build and optimize the technical foundations that power model improvement for foundation model builders and leading labs. This role is ideal for someone who has hands-on experience fine-tuning and evaluating large language models (and ideally multimodal models), and who can bridge research and engineering in real-world customer environments. You will work closely with Language Data Scientists, Applied Research Scientists, data engineers, and client technical stakeholders to design and implement robust training/evaluation pipelines using both human-in-the-loop and AI-augmented methods. What You’ll Own - Design and implement the pipelines and tooling that connect data, evaluation, and post-training. - Help customers and internal teams move from evaluation findings to measurable model improvements. - Build fine-tuning workflows (e.g., supervised fine-tuning and preference-based optimization). - Integrate evaluation harnesses into model development loops. - Improve experiment reliability and throughput. - Support advanced evaluation scenarios such as long-context, cross-modal, and dynamic multi-turn interactions. - Contribute to Innodata’s internal R&D efforts, including benchmark datasets, evaluation frameworks, and reusable infrastructure for model assessment and post-training experimentation. - Lead or co-lead technically complex ML engineering projects from initial customer discussions through implementation and delivery. - Design, build, and improve LLM training and post-training pipelines, including data ingestion, preprocessing, fine-tuning, evaluation, and experiment tracking. - Implement and optimize evaluation systems for LLMs and multimodal models, including offline benchmarks and task-specific test harnesses. - Integrate human-in-the-loop and AI-augmented evaluation signals into model development workflows. - Build robust infrastructure and tooling for reproducible experimentation, metrics logging, and regression monitoring. - Diagnose model behavior and pipeline failures, including data issues, training instability, metric inconsistencies, and evaluation drift. - Collaborate with Language Data Scientists and Applied Research Scientists to translate evaluation frameworks into executable systems. - Work closely with customer technical stakeholders to understand goals, constraints, and success criteria; propose and implement technically sound solutions. - Contribute to internal research and platform development, including benchmark frameworks, evaluation tooling, and post-training workflow improvements. - Contribute to best practices and standards for LLM training, evaluation, and quality assurance across projects. - Mentor junior engineers and contribute to technical design reviews, documentation, and engineering rigor across the team. Qualifications - BS/MS/PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or a related quantitative technical field (MS/PhD preferred). - 2-3 years of relevant industry or research engineering experience in ML/AI systems. - Hands-on experience with LLM training / fine-tuning / post-training, including at least one of: - supervised fine-tuning (SFT) - preference optimization (e.g., DPO or related methods) - RLHF / RLAIF-style workflows - task- or domain-adaptation of foundation models - Strong programming skills in Python and experience building production-quality ML code. - Experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow) and model libraries/tooling (e.g., Hugging Face ecosystem, vLLM, distributed training stacks). - Experience designing and implementing evaluation pipelines for LLM/ML systems, including metrics computation, dataset handling, and experiment comparisons. - Strong understanding of data pipelines and ML systems engineering, including reproducibility, observability, and debugging. - Experience with large-scale distributed ML systems and performance optimization for training/evaluation workloads (GPU/accelerator environments preferred). - Experience with large-scale data processing and workflow orchestration in support of model training/evaluation. - Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data engineers, and customer technical leads. - Strong written and verbal communication skills, including the ability to explain complex technical tradeoffs to both technical and non-technical audiences. Technical Skills - ML / LLM Engineering - Experience training, fine-tuning, and evaluating transformer-based models. - Understanding of post-training workflows and model iteration loops. - Familiarity with inference-time considerations (latency, throughput, memory/performance tradeoffs) where relevant to evaluation or deployment. - Evaluation & Experimentation - Experience implementing automated evaluation pipelines and test harnesses. - Experience with experiment tracking, versioning, and reproducibility practices. - Ability to assess metric quality and ensure consistency across model comparisons. - Software / Data Engineering - Proficiency in Python and strong software engineering fundamentals. - Experience with data processing pipelines, storage formats, and scalable dataset workflows. - Familiarity with CI/CD, testing, and engineering quality practices for ML systems. Salary Range The expected salary range for this position is $80,000 – $175,000 USD per year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams . If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description As a Software Development Engineer in Test (SDET) at Ordermesh Inc, you will be a key force in evolving our automation-first quality culture across a complex microservices platform (Kafka, NoSQL, REST APIs, async workflows). The role is less about manual gatekeeping and more about building CI-integrated quality pipelines that let developers ship confidently and independently. It's for someone who wants to own the full automation strategy — from build-time testing to real-time quality metrics. What You’ll Do - Champion an automation-first mindset; manual testing should be the exception, not the rule. - Design, build, and scale automated test frameworks for APIs, UI, and end-to-end microservice validation using Node.js, Playwright, and related frameworks. - Develop load and resilience testing suites with Grafana k6 to benchmark and harden distributed systems. - Integrate test execution and quality gates deeply into GitHub Actions, ensuring every commit, PR, and deployment is validated by automation. - Collaborate closely with MCPs: Kafka event flows, service mesh routing (Istio), and inter-service contracts to design automated validation of message schemas, ACLs, and service dependencies. - Mock endpoints with services like microcks or postman to simulate responses. - Lead TDD adoption by embedding test scaffolds into developer workflows and enforcing test coverage standards across repositories. - Embed security testing and data validation checks into automation frameworks for proactive vulnerability detection. - Create test observability dashboards (via Grafana or Datadog) that expose quality metrics alongside performance and error budgets. - Perform exploratory testing to supplement automation with contextual discovery and edge-case validation. - Collaborate with developers, SREs, and product managers to drive a shared understanding of quality across environments. Qualifications - 5+ years of hands-on experience building and maintaining automated test frameworks for microservice and web applications. - Strong proficiency in Node.js, JavaScript/TypeScript, or equivalent modern language. - Demonstrated experience integrating tests into CI/CD systems; ideally GitHub Actions, Jenkins, or Azure DevOps. - Proven track record in load testing (Grafana k6) and performance analysis at scale. - Experience validating MCP integrations including: message brokers (Kafka), service meshes (Istio), and REST/gRPC endpoints. - Working knowledge of Playwright or similar browser automation frameworks. - Understanding of TDD, security testing, and DevSecOps principles. - Excellent debugging, observability, and root-cause analysis skills. - Bachelor's degree in Computer Science or equivalent practical experience. - Passion for driving automation-first culture and mentoring others in modern test engineering practices. Bonus Qualifications - Experience with Azure, Kubernetes, and containerized CI environments. - Familiarity with contract testing frameworks for validating MCP communication. - Experience with Grafana, Datadog, or similar platforms for system and test observability. - Familiarity with B2B, eCommerce, or fulfillment ecosystems.