AI Machine Learning Engineer Job at York Solutions, LLC in Chicago
York Solutions, LLC, Chicago, IL, United States
Description Logistics
Type: 6+ month contract to hire (C2H is a must have). Location: Willis Tower, downtown Chicago, IL - 5 days on-site, after conversion only 4 days on-site required.
Team Overview
This team is looking for someone passionate about machine learning who can join a startup-like division. They are on the cutting edge of AI initiatives. This team supports many ongoing AI initiatives all centered around medical devices, so healthcare/med device/pharma experience is highly preferred.
Role Summary
Drive the technical execution of AI initiatives by bridging advanced algorithm research with scalable engineering. You will own the completion and future evolution of the PAI AI Development foundation, stand-up production‑grade MLOps, and act as the connective tissue between data, infrastructure, and algorithm teams.
Key Responsibilities
End‑to‑end design & delivery of ML solutions (data ingestion, feature engineering, training, validation, deployment, monitoring).
Architecting a highly available, secure, cloud/on‑prem hybrid ML infrastructure.
Lead implementation of CI/CD for models (testing, rollout, rollback, governance).
Partner with algorithm scientists to translate ideas into production‑ready code.
Ensure regulatory & privacy compliance (HIPAA, GDPR, SaMD) in pipelines.
Evaluate emerging GenAI tools, multimodal techniques, and HW accelerators; pilot where valuable.
Mentor scientists and engineers, establish coding standards, and conduct design reviews.
Required Qualifications
8+ yrs software / ML engineering, incl. 3+ yrs architecting production ML systems.
Strong domain knowledge and experience in medical signal and image processing.
Background or experience with medical devices is strongly preferred.
Deep expertise in Python; proficiency in one systems language (C++/Go/Java).
Strong working knowledge of PyTorch/TensorFlow/JAX, distributed training, and GPU optimization.
Hands‑on with Docker, Kubernetes, ML orchestration (Kubeflow, Airflow, Prefect), and model registries (MLflow).
Experience operating in a regulated or mission‑critical environment.
Proven record of leading project teams or mentoring ML scientists and engineers; comfortable making architectural decisions and rallying others around them.
Preferred Qualifications
Background in signal processing, computer vision, or multimodal learning.
Prior involvement in FDA 510(k) / SaMD submissions or clinical‑grade ML products.
Experience with data security, anonymization, synthetic data, and federated learning.
Publications, patents, or open‑source leadership are a plus.
Demonstrated ability to scale yourself through others — e.g., setting coding standards, running design reviews, or leading guilds/chapters.
Soft Skills: Strategic mindset, bias for action, excellent written & verbal communication, team‑first attitude.
Benefits
BCBS Medical with 3 plans to choose from (PPO and high‑deductible PPO plans with Health Savings Program).
Delta Dental plan with 2 free cleanings and insurance discounts.
EyeMed Vision with annual check‑ups and discounts on lenses.
Life and accidental death insurance paid by company.
John Hancock 401(k) retirement plan with discretionary company match.
Voluntary insurance programs such as hospital indemnity, identity protection, legal insurance, long‑term care, and pet insurance.
Flexible work environment with some remote working opportunities.
Strong fun and teamwork environment.
Learning, development, and career growth.
#J-18808-Ljbffr
In Summary: This team is looking for someone passionate about machine learning who can join a startup-like division . This team supports many ongoing AI initiatives all centered around medical devices . Healthcare/med device/pharma experience is highly preferred . Strong domain knowledge and experience in medical signal and image processing .
En Español: Descripción Tipo de logística: 6+ meses contrato para contratar (C2H es una necesidad). Localización: Willis Tower, centro de Chicago, IL - 5 días en el sitio, después de la conversión sólo 4 días en lugar requerido. Usted será propietario de la finalización y evolución futura de la fundación PAI AI Development, MLOps stand-up de nivel de producción y actuará como el tejido conectivo entre los equipos de datos, infraestructura y algoritmos. Responsabilidades claves Diseño de extremo a extremo y entrega de soluciones ML (ingestión de información, ingeniería de características, capacitación, validación, despliegue, monitoreo). Arquitectura de una infraestructura ML híbrida altamente disponible, segura, en la nube / on-premise. Implementación líder de CI/CD para modelos (testaje, lanzamiento, retroceso, gobernanza). Conocimiento de dominio y experiencia en el procesamiento de señales e imágenes médicas. Se prefieren fuertes conocimientos o experiencias con dispositivos médicos. Experimentación profunda en Python; competencia en un lenguaje de sistemas (C++/Go/Java). Fuerte conocimiento laboral de PyTorch / TensorFlow/JAX, capacitación distribuida y optimización de GPU. Mano a mano con Docker, Kubernetes, orquestación ML (Kubeflow, Airflow , Prefect) y registros de modelos (MLflow). Experiencia operando en un entorno regulado o misional es preferible. Prueba probada de equipos líderes de proyectos o científicos y mentores del aprendizaje ML-1880; decisiones arquitectónicas cómodas y reuniones alrededor de otros. Qualificaciones Preferidas Proyectos profesionales en los estándares de señal, visión remota o aprendizaje verbal Prioridad 401 .
Type: 6+ month contract to hire (C2H is a must have). Location: Willis Tower, downtown Chicago, IL - 5 days on-site, after conversion only 4 days on-site required.
Team Overview
This team is looking for someone passionate about machine learning who can join a startup-like division. They are on the cutting edge of AI initiatives. This team supports many ongoing AI initiatives all centered around medical devices, so healthcare/med device/pharma experience is highly preferred.
Role Summary
Drive the technical execution of AI initiatives by bridging advanced algorithm research with scalable engineering. You will own the completion and future evolution of the PAI AI Development foundation, stand-up production‑grade MLOps, and act as the connective tissue between data, infrastructure, and algorithm teams.
Key Responsibilities
End‑to‑end design & delivery of ML solutions (data ingestion, feature engineering, training, validation, deployment, monitoring).
Architecting a highly available, secure, cloud/on‑prem hybrid ML infrastructure.
Lead implementation of CI/CD for models (testing, rollout, rollback, governance).
Partner with algorithm scientists to translate ideas into production‑ready code.
Ensure regulatory & privacy compliance (HIPAA, GDPR, SaMD) in pipelines.
Evaluate emerging GenAI tools, multimodal techniques, and HW accelerators; pilot where valuable.
Mentor scientists and engineers, establish coding standards, and conduct design reviews.
Required Qualifications
8+ yrs software / ML engineering, incl. 3+ yrs architecting production ML systems.
Strong domain knowledge and experience in medical signal and image processing.
Background or experience with medical devices is strongly preferred.
Deep expertise in Python; proficiency in one systems language (C++/Go/Java).
Strong working knowledge of PyTorch/TensorFlow/JAX, distributed training, and GPU optimization.
Hands‑on with Docker, Kubernetes, ML orchestration (Kubeflow, Airflow, Prefect), and model registries (MLflow).
Experience operating in a regulated or mission‑critical environment.
Proven record of leading project teams or mentoring ML scientists and engineers; comfortable making architectural decisions and rallying others around them.
Preferred Qualifications
Background in signal processing, computer vision, or multimodal learning.
Prior involvement in FDA 510(k) / SaMD submissions or clinical‑grade ML products.
Experience with data security, anonymization, synthetic data, and federated learning.
Publications, patents, or open‑source leadership are a plus.
Demonstrated ability to scale yourself through others — e.g., setting coding standards, running design reviews, or leading guilds/chapters.
Soft Skills: Strategic mindset, bias for action, excellent written & verbal communication, team‑first attitude.
Benefits
BCBS Medical with 3 plans to choose from (PPO and high‑deductible PPO plans with Health Savings Program).
Delta Dental plan with 2 free cleanings and insurance discounts.
EyeMed Vision with annual check‑ups and discounts on lenses.
Life and accidental death insurance paid by company.
John Hancock 401(k) retirement plan with discretionary company match.
Voluntary insurance programs such as hospital indemnity, identity protection, legal insurance, long‑term care, and pet insurance.
Flexible work environment with some remote working opportunities.
Strong fun and teamwork environment.
Learning, development, and career growth.
#J-18808-Ljbffr
In Summary: This team is looking for someone passionate about machine learning who can join a startup-like division . This team supports many ongoing AI initiatives all centered around medical devices . Healthcare/med device/pharma experience is highly preferred . Strong domain knowledge and experience in medical signal and image processing .
En Español: Descripción Tipo de logística: 6+ meses contrato para contratar (C2H es una necesidad). Localización: Willis Tower, centro de Chicago, IL - 5 días en el sitio, después de la conversión sólo 4 días en lugar requerido. Usted será propietario de la finalización y evolución futura de la fundación PAI AI Development, MLOps stand-up de nivel de producción y actuará como el tejido conectivo entre los equipos de datos, infraestructura y algoritmos. Responsabilidades claves Diseño de extremo a extremo y entrega de soluciones ML (ingestión de información, ingeniería de características, capacitación, validación, despliegue, monitoreo). Arquitectura de una infraestructura ML híbrida altamente disponible, segura, en la nube / on-premise. Implementación líder de CI/CD para modelos (testaje, lanzamiento, retroceso, gobernanza). Conocimiento de dominio y experiencia en el procesamiento de señales e imágenes médicas. Se prefieren fuertes conocimientos o experiencias con dispositivos médicos. Experimentación profunda en Python; competencia en un lenguaje de sistemas (C++/Go/Java). Fuerte conocimiento laboral de PyTorch / TensorFlow/JAX, capacitación distribuida y optimización de GPU. Mano a mano con Docker, Kubernetes, orquestación ML (Kubeflow, Airflow , Prefect) y registros de modelos (MLflow). Experiencia operando en un entorno regulado o misional es preferible. Prueba probada de equipos líderes de proyectos o científicos y mentores del aprendizaje ML-1880; decisiones arquitectónicas cómodas y reuniones alrededor de otros. Qualificaciones Preferidas Proyectos profesionales en los estándares de señal, visión remota o aprendizaje verbal Prioridad 401 .