Search Results for "Jenkins"

The **Synthetic Data Specialist** designs, generates, validates, and operationalizes **synthetic datasets** that safely replicate the statistical and structural properties of sensitive or scarce real data. The role enables teams to train, test, and analyze AI/ML systems while reducing exposure to regulated data (e.g., PII) and accelerating development cycles through faster, safer data access.

The **Senior Robotics Specialist** is a senior individual contributor in the **AI & ML** department responsible for designing, integrating, validating, and operationalizing robotics capabilities that combine perception, planning, control, and safe real-world execution. This role translates business requirements into reliable robotic behaviors and deployable autonomy software, working across simulation, edge compute, and cloud-based orchestration.

The **Senior Model Evaluation Specialist** designs, executes, and operationalizes rigorous evaluation of machine learning (ML) and generative AI models to ensure they are accurate, reliable, safe, and fit for production use. This role turns ambiguous product and risk questions (“Is the model good enough?”, “Is it safe?”, “Will it regress?”) into measurable criteria, repeatable test suites, and decision-ready insights.

The **Senior Machine Learning Specialist** is a senior individual contributor responsible for designing, building, validating, and operating machine learning solutions that measurably improve software products and internal platforms. The role bridges applied research and production engineering by translating business needs into robust ML systems, ensuring models are accurate, reliable, cost-effective, and governable at scale.

The **Senior Autonomous Systems Specialist** designs, validates, and operationalizes software autonomy capabilities—planning, decision-making, and closed-loop control—so products and platforms can act reliably with minimal human intervention in dynamic environments. This role sits at the intersection of **AI/ML, real-time software engineering, simulation, and safety-oriented engineering**, converting research-grade autonomy approaches into production-grade systems with measurable reliability.

The **Robotics Specialist** designs, integrates, and operationalizes robotics software capabilities—spanning perception, planning, control, simulation, and fleet operations—so robotic systems can perform reliably in real-world environments. This is an **individual contributor (IC)** specialist role, typically mid-level, positioned in an **AI & ML department** within a software company or IT organization that develops and/or operates robotics-enabled products, platforms, or internal automation solutions.

The Model Evaluation Specialist designs, executes, and operationalizes rigorous evaluation of machine learning (ML) and increasingly large language models (LLMs) across offline benchmarks, pre-production testing, and post-deployment monitoring. The role exists to ensure models are **measurably effective, safe, reliable, and aligned with product intent**, and that model quality is assessed consistently over time as data, prompts, and user behavior evolve.

The **Machine Learning Specialist** designs, builds, evaluates, and operationalizes machine learning solutions that deliver measurable product and business outcomes in a software or IT organization. This role focuses on translating well-scoped business problems into reliable ML systems, partnering closely with engineering, data, and product teams to move models from experimentation into production with appropriate monitoring and governance.

The **Lead Synthetic Data Specialist** designs, builds, validates, and operationalizes synthetic data capabilities that enable AI/ML development, testing, and analytics when real data is scarce, sensitive, regulated, or costly to access. This role owns the end-to-end synthetic data lifecycle—from problem framing and privacy risk analysis through generation methods, utility evaluation, and production-grade delivery via governed pipelines.

The **Lead Robotics Specialist** is a senior individual-contributor (IC) technical leader responsible for designing, integrating, and operationalizing robotics capabilities that are tightly coupled with AI/ML systems—typically spanning perception, autonomy, motion planning, simulation, and fleet/edge operations. This role exists in a software or IT organization to ensure robotics initiatives transition from prototype to reliable, secure, supportable products and platforms that can be deployed and managed at scale.

The **Lead Model Evaluation Specialist** is a senior individual contributor who designs, standardizes, and operationalizes how machine learning (ML) and AI models are evaluated before and after release. The role exists to ensure models are **measurably effective, reliable, safe, and aligned to product outcomes**, using robust evaluation methodologies, test harnesses, and monitoring practices that scale across teams.

The **Lead Machine Learning Specialist** is a senior individual contributor who designs, delivers, and operationalizes machine learning solutions that materially improve product capabilities and internal decision-making. The role combines advanced applied ML expertise with technical leadership across the full lifecycle—problem framing, data and feature strategy, model development, evaluation, deployment, monitoring, and iteration—while ensuring solutions are reliable, scalable, and responsibly governed.

The **Lead Autonomous Systems Specialist** is a senior individual contributor who designs, prototypes, validates, and operationalizes autonomous capabilities—such as perception, prediction, planning, control, and autonomous decision-making—within production-grade software systems. The role bridges advanced AI/ML methods with safety-aware engineering practices to deliver autonomy that is measurable, testable, and deployable at scale.

The **Autonomous Systems Specialist** designs, implements, validates, and operates software that enables **systems to perceive context, decide, and act with minimal human intervention** while meeting safety, reliability, and performance expectations. In a software company or IT organization, this role exists to translate emerging autonomy techniques (e.g., planning, reinforcement learning, perception, agentic orchestration) into **production-grade capabilities** that can be deployed, monitored, and continuously improved.

The **Associate Robotics Specialist** is an early-career, hands-on specialist who supports the development, testing, integration, and reliable operation of robotics software components within an **AI & ML** organization. The role focuses on building and validating robotics capabilities (e.g., perception, navigation, sensor integration, simulation-to-real workflows, and fleet telemetry) under the guidance of senior robotics engineers and applied ML leaders.

The **Associate Model Evaluation Specialist** helps ensure machine learning (ML) and AI model outputs are **measured, trustworthy, and release-ready** by designing and executing evaluation plans, maintaining evaluation datasets, and producing clear, decision-useful performance insights. This role sits in an **AI & ML** department within a software or IT organization and focuses on **systematic model testing** across accuracy, robustness, fairness, reliability, and business impact.

The **Associate Machine Learning Specialist** is an early-career individual contributor in the AI & ML department who supports the design, development, evaluation, and operationalization of machine learning solutions in a software or IT organization. The role focuses on reliable execution: building datasets, prototyping models, running experiments, implementing baseline pipelines, and contributing to production-readiness under guidance from senior ML engineers, data scientists, or an ML engineering manager.

The **Associate Autonomous Systems Specialist** supports the design, implementation, testing, and operational monitoring of **autonomous system capabilities**—software components that can **sense, decide, and act** with limited human intervention. In a software or IT organization, this typically includes autonomy features such as **agentic workflows**, **policy-constrained decision logic**, **closed-loop automation**, **reinforcement-learning-informed strategies**, and **safety guardrails** integrated into production services.