Machine Learning Engineer

Own the DocV forensic engine roadmap.

Scale DocV adoption across multiple sectors.

Lead and grow a team of ML engineers.

Define vision and roadmap for cart perception.

To design and implement AI algorithms.

To collaborate with teams for AI integration.

Lead and manage teams in CV and ML.

Architect and enhance hybrid cloud-edge ML solutions.

Lead teams in CV and ML development.

Architect hybrid cloud-edge ML solutions.

Lead the development of computer vision systems.

Manage and mentor engineering teams across locations.

Develop computer vision product strategies.

Lead cross-functional teams in product execution.

Lead research in computer vision.

Develop image and video models.

Develop multimodal vision-language systems.

Enhance patient perception through video, language, and speech.

Develop robotic software for agricultural systems.

Enhance ML pipelines and AI features.

Enhance computer vision components.

Develop biometric features using CV and ML.

Conduct research on vision-language-action modeling.

Deploy AI solutions in real-world robotics.

Develop a multi-modal foundation encoder.

Enhance 3D object detection and tracking capabilities.

Design and deploy computer vision models.

Manage end-to-end ML pipeline.

Own technical delivery across deployments.

Understand customer workflows and requirements.

Coordinate with leads to prioritize impactful developments.

Evaluate requirements and enhance team tools/processes.

Build and manage a machine learning team.

Set technical standards for hiring and performance.

Align middleware and safety design requirements.

Maintain an architecture view of the middleware stack.

Build and scale systems for real-time radio traffic.

Develop software for edge devices and cloud backend.

Develop avionics systems from concept to hardware.

Collaborate with various engineering teams.

Own avionics design and delivery.

Collaborate with various engineering teams.

Own complex features from design to production.

Design and maintain core Roku platform software.

Develop and extend firmware for photonic devices.

Define control plane architecture for interconnects.

Drive architecture across OS client stack.

Optimize performance on embedded hardware.

Lead machine learning and signal processing teams.

Define roadmap for algorithm systems.

Coordinate and complete complex customer-facing projects.

Act as the primary liaison between engineering teams and customers.

Manage execution pipeline for hardware programs.

Lead and mentor firmware engineering teams.

Lead and manage the flight software engineering team.

Set technical direction and architecture for flight software.

Define product vision for AI-powered devices.

Drive new product initiatives from ideation to launch.

Hire a remote Principal AI Engineer

Develop customer experience automation solutions

Design and implement ML systems|Apply optimization strategies|Collaborate with teams|Analyze data

r user behavior|Develop data

Revolutionize enterprise data operations through AI solutions.

Automate and accelerate data tasks for overworked data teams.

Hire a remote Senior Data Scientist

Enhance product with data-driven insights

Develop scalable backend solutions

Mentor team members

Lead development of scalable ML systems

Advance Apollo's AI-native product features

Design and productionize scalable machine learning systems

Personalize user experiences using data-driven models

Build and productionize Machine Learning models for Apollo products

Optimize users' experience at all stages of their product journey

. Lead and manage the AI Team effectively

. Drive innovation in AI technologies

Drive AI quality in collaboration products

Lead remote cross-functional teams

Lead AI-focused design initiatives

Manage and mentor remote design teams

Hire a remote senior data scientist

Promote a flexible, location-independent role

Guide customers through product journey

Build custom demos and prototypes

Provide technical leadership in data science

Develop and implement advanced analytics models

Drive cross-functional data initiatives

Collaborate with various teams to uncover insights

Drive data-driven strategies for product development.

Enhance business and customer impact through data analysis.

Lead HR transformation through Workday optimization

Guide cross-functional teams in complex Workday changes