Freelance Electrical Engineer with Python Experience - 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.
Freelance Electrical Engineering & Python Expert - 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 that scenarios are production-ready, easy to run, and reusable.
Freelance Electrical Engineering & Python Expert - 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.
(Senior) Systems Safety Engineer
At Helsing, the Systems Safety Engineer is responsible for developing machine learning and artificial intelligence systems that leverage and extend the latest state-of-the-art methods and architectures. They design experiments and conduct benchmarks to evaluate and improve AI performance in real-world scenarios. The role involves collaboration with teams from multiple backgrounds to integrate cutting-edge ML/AI into production systems that support semi-autonomous platforms in localisation, navigation, and perception in real time, with a focus on robustness against adversarial attacks and safety.
Intern: Robotic Systems Development Workflows
Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate concepts into robust capabilities deployable on physical robotic hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.
Forward Deployed Engineer (FDE), Life Sciences - Munich
Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows. Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints. Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until sustained production impact is demonstrated. Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling. Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes. Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.
Freelance Machine Learning Engineer (Python)
Design original computational STEM problems that simulate real scientific workflows. Create problems requiring Python programming to solve. Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes of days or weeks. Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches. Verify solutions using Python with standard libraries such as numpy, pandas, scipy, and sklearn. Document problem statements clearly and provide verified correct answers.
Freelance Machine Learning AI Trainer (Python)
Design original computational STEM problems that simulate real scientific workflows. Create problems that require Python programming to solve. Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches. Verify solutions using Python with standard libraries (numpy, pandas, scipy, sklearn). Document problem statements clearly and provide verified correct answers.
Safety Engineer
The AI Safety Engineer is responsible for designing and building scalable backend infrastructure for content moderation, abuse detection, and agents guardrails by deploying AI/ML models into production systems. They will architect robust APIs, data pipelines, and service architectures to support real-time and batch moderation workflows. The role includes implementing comprehensive monitoring, alerting, and observability systems, establishing SLIs, SLOs, and performance benchmarks. The engineer will collaborate with ML engineers to translate research models into production-ready systems and integrate them across the product suite. Additionally, they will drive technical decisions and contribute to the vision for the safety roadmap to build next-generation platform guardrails for scale and precision.
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