Mechanical Engineer with Python Experience - Freelance AI Trainer
Contributors may design graduate- and industry-level mechanical engineering problems grounded in real practice, evaluate AI-generated solutions for correctness, assumptions, and engineering logic, validate analytical or numerical results using Python (NumPy, SciPy, Pandas), improve AI reasoning to align with first principles and accepted engineering standards, and apply structured scoring criteria to assess multi-step problem solving.
Security engineer, application security (UK)
As a security engineer, applications at WRITER, you will build the security foundations protecting AI systems used by major brands. Responsibilities include conducting threat modeling sessions with product teams, designing secure architectures for new features, and ensuring security considerations are integrated from the start of product development. You will own and evolve the application security program, establish and maintain SAST/DAST scanning in CI/CD pipelines, perform security code reviews for critical changes, and build automation to detect vulnerabilities before production. You will partner with engineering teams to establish secure coding standards, create reusable security patterns and libraries, and design security features to protect customer environments. Integrating AI agents to improve security team efficiency, leading security assessments and penetration testing of applications, AI services, and APIs, as well as designing and implementing security controls for data pipelines, model training, and customer AI agents are also key duties. Additionally, you will research emerging threats specific to AI/ML security and build defenses against new risks.
Mission Manager - International Government
Use proprietary software applications to provide input and labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives and technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from corporate accounting fields that align with your expertise, providing rigorous solutions and model critiques. Regularly interpret, analyze, and execute tasks based on given instructions. Participate in gathering or providing data such as text, voice, and video data, provide annotations, recording audio, or participating in video sessions as fundamental parts of the role, ensuring alignment with xAI’s goals to innovate.
QA Engineer, AI
The QA Engineer, AI is responsible for owning and expanding the end-to-end automated test suite using frameworks like Playwright, Jest, and Vitest across all deployment surfaces including web app, iPad, Epic, Cerner, Surgery Connect, EMIS, and multiple browsers. They design test cases covering functional requirements, edge cases, and failure modes, integrate tests into CI pipelines to gate every PR, and use AI coding agents to accelerate test creation and maintenance. They build end-to-end simulation suites for clinical AI pipeline evaluation, create smoke tests, collaborate with the ML team on AI output evaluations, and detect quality regressions. The role involves managing the QA process for versioned releases, running regression and manual exploratory tests, managing release checklists, maintaining requirements traceability matrices linking software requirements to test cases and results, supporting audits with documentation, automating compliance workflows, logging and triaging defects, working with developers to reproduce issues and verify fixes, and ensuring no high-severity defects ship without resolution and re-testing.
Solutions Architect
The Solutions Architect is responsible for designing scalable, highly-available infrastructure for AI platform deployments including compute, storage, networking, security, enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines. They design multi-agent systems using different patterns, implement agent logic with frameworks like langchain/langgraph, design evaluation frameworks, optimize prompts with A/B testing, and guide deployment and operations. The role involves leading technical maturity assessments, working directly with enterprise customers to understand requirements and provide recommendations, and partnering with Engagement Managers and Product/Engineering teams. Responsibilities combine software development, infrastructure/platform engineering, and customer-facing skills focusing on Kubernetes cluster design to multi-agent system architecture to solve real business problems.
Senior Manager
Lead transformational AI system implementations by scoping high-value solutions and navigating complex technical challenges alongside technical colleagues. Manage enterprise life sciences accounts, including oversight of pricing, contract negotiations, resourcing, and identifying strategic growth opportunities. Build deep trust with senior stakeholders in global enterprises through understanding how Frontier addresses their operational problems. Advocate for customer needs internally by providing product development teams with direct insights to refine and enhance the platform. Create scalable delivery assets such as playbooks and process improvements to empower external partners and internal teams. Collaborate across functions including engineering, data science, and business development to explore novel use cases and ensure seamless project coordination.
Healthcare & life sciences AI agent analyst (contract)
Develop and implement AI agents for life sciences applications, including medical writing assistants, literature synthesis tools, regulatory document preparation systems, and research protocol generators. Design and execute comprehensive testing protocols to evaluate AI agent performance, scientific accuracy, and adherence to medical writing standards across diverse research and regulatory scenarios. Collaborate with Customer Operations and Life Sciences Industry leaders to translate research workflows, regulatory requirements, and publication standards into functional AI agent specifications. Guide technical and engineering teams in implementing best practices for medical AI development, including prompt engineering, retrieval-augmented generation, and scientific validation methodologies. Potential additional responsibilities include architecting and deploying multi-agent systems to orchestrate complex research workflows, leading research initiatives on novel applications of generative AI in medical writing, drug development, and scientific research, publishing findings, and providing training and mentorship on life sciences AI development principles, scientific integrity considerations, and regulatory compliance.
Hardware Engineer, Silicon Design
Define and implement microarchitecture for novel AI accelerator blocks by collaborating closely with architecture and research teams to translate algorithmic requirements into efficient hardware implementations. Write high-quality RTL in SystemVerilog for core logic, datapaths, and control structures optimized for AI/ML workloads. Stay current with state-of-the-art AI algorithms and architectures, understanding their computational patterns and hardware implications. Analyze existing AI accelerator architectures and apply lessons learned to new design problems. Work with the DV team on digital verification for assigned designs, including testbench development, debugging, coverage, and signoff. Collaborate with physical design engineers to ensure RTL is implementable, performant, and aligned with layout constraints. Contribute to functional or performance models to support early exploration, validation, and design tradeoff analysis. Participate in design reviews, verification reviews, and cross-functional debug from concept through silicon.
Freelance Electrical Engineer with Python Experience - AI Trainer
Contributors may design rigorous electrical engineering problems reflecting professional practice, evaluate AI solutions for correctness, assumptions, and constraints, validate calculations or simulations using Python (NumPy, Pandas, SciPy), improve AI reasoning to align with industry-standard logic, and apply structured scoring criteria to multi-step problems.
Evaluation Scenario Writer - AI Agent Testing Specialist
Contributors may create structured test cases that simulate complex human workflows, define gold-standard behavior and scoring logic to evaluate agent actions, analyze agent logs, failure modes, and decision paths, work with code repositories and test frameworks to validate scenarios, iterate on prompts, instructions, and test cases to improve clarity and difficulty, and ensure scenarios are production-ready, easy to run, and reusable.
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