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.
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.
Freelance Electrical Engineering & Python Expert - AI Trainer
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. Apply structured scoring criteria to multi-step problems.
Freelance Electrical Engineering & Python Expert - AI Trainer
Contributors 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.
Software Engineer II (India - Bangalore)
Engineers at Giga work on problems like building AI agents with almost no hallucination rates, creating a voice experience that is better than talking to humans, and creating self-learning agents that optimize metrics.
Data Scientist
Collect, process, and analyze large datasets from multiple sources Build and deploy machine learning models to solve business problems Design and implement A/B tests and statistical analyses Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements Communicate complex data insights in a clear and actionable manner to stakeholders Develop dashboards and visualizations to monitor key metrics Stay current with the latest trends and technologies in data science and AI
Software Engineer III
As a Software Engineer III at HackerOne, you will work closely with senior engineers, Product Managers, Designers, and customer operations teams across different locations to solve real-world problems for global customers. Your responsibilities include delivering end-to-end meaningful features and components, proactively managing dependencies, improving planning and execution to reduce rework, and contributing to the Continuous Threat Exposure Management (CTEM) roadmap by building agentic capabilities that combine AI with secure, reliable product experiences focused on customer outcomes and measurable impact. You will identify and improve technical weaknesses in codebases both within your squad and company-wide, build, ship, and maintain highly available and performant features especially in hacker-facing platform areas, drive predictable delivery by removing blockers and managing dependencies, participate in cross-squad initiatives to improve team throughput and quality, mentor and be mentored by other engineers, and contribute to AI-assisted and agentic workflows development by applying data-driven iteration and first principles thinking to simplify systems and avoid fragile quick fixes.
Senior Software Engineer
The Senior Software Engineer will work closely with senior engineers, Product Managers, Designers, and Customer Operations teams across multiple locations to solve real-world problems for global customers. They will lead complex initiatives and own end-to-end delivery of projects with moderate to large scope, anticipating delivery risks, aligning stakeholders early, and maintaining quality under tight timelines. Responsibilities include driving the design and delivery of AI-assisted and agentic capabilities tied to customer outcomes, raising the bar for platform health, influencing engineering practices to accelerate execution, identifying and making systematic improvements to technical weaknesses in the codebases across the company, leading CTEM and agentic work including architecture for agentic workflows, building AI tools to improve delivery efficiency and reduce repetitive work, proactively leading adaptation during change, and implementing data loops for continuous optimization. They will also onboard, guide, mentor, and delegate to engineers while creating clarity, reusable patterns, and strong technical direction, participate in cross-squad initiatives to influence shared engineering practices, and deliver key results for impactful objectives by balancing scope, risk, and speed while raising risks early and creating shared context for the importance of the work against team goals and roadmap.
AI / ML Solutions Engineer
The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.
Software Engineer, macOS Core Product - Virginia Beach, USA
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, then design and implement solutions addressing the highest priority issues.
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