Staff Computer Vision and Machine Learning Engineer

As a StaffComputer Vision and Machine Learning Engineer you will serve as a technical lead through the design development and deployment of advanced computer vision and machine learning models across the business. This role focuses on building scalable computer vision and machine learning models mentoring junior engineers and driving the full lifecycle of computer vision and machine learning model development.

You will be the technical lead for a team of Computer Vision and Machine Learning engineers and/or data scientists focused on ensuring that computer vision and machine learning models are robust high-performing and seamlessly integrated into production systems. This position involves both hands-on engineering work and leadership responsibilities in a dynamic environment.

• Design and implement computer vision and machine learning models and components that solve real-world business problems in close collaboration with Productbusiness units and Data Science teams.

• Write production-grade code for ML models as services and APIs.

• Collaborate with cross-functional teams including data engineering and software development to integrate computer vision and machine learning models into production systems.

• Build andmaintainscalable data processing workflows and model deployment infrastructure.

• Debug and resolve model performance issues track relevant metrics and implement continuous improvements to ensure model accuracy and reliability.

• Keep up with the latestCV andML tooling and communities.

• Lead the design and implementation of complex computer vision and machine learning models across various business units.

• Architect and develop scalable infrastructure for automated model training hyperparameter tuning and deployment.

• Mentor and guide junior engineers collaborating closely with computer vision and machine learning engineers tooptimizeand refine models.

• Own the end-to-end systems for model monitoring maintenance and retraining to ensure high availability and performance.

• B.S. incomputer science computer & electrical engineering or related discipline M.S. incomputer visionmachine learning Computer Science Statistics Mathematics or a related quantitative fieldor equivalent work experience in CV domain (see below).

• 6 years of experience applying computer vision and machine learning techniques such as ensemble learning deep learning reinforcement learning NLP or related approaches.

• Direct work experience in CV discriminative models (detection segmentation) CV foundation models VLM MLLMs generative tools (diffusers).

• 6 years of experience with SQL Spark(or equivalent) and Pythoncomputer visionand machine learning frameworks such as TensorFlowPyTorch and Scikit-learn.

• 4 years of experience working with cloud platformsand environments such as AWS Microsoft Azure Databricksand/or Snowflakeand Kubernetes.

• 4 years of experience applying computer vision and machine learning techniques in a production environment for business solutions.

• Nice tohave:publication(s) in top CVconference(CVPR ICCV ECCVetc)

Computer Vision and Machine Learning and Statistical Modeling

• Strong foundationin advanced computer vision and machine learning algorithms including supervised and unsupervised learning techniques as well as familiarity with generative models.

• Proficiencyin statistical modeling including probability theory and hypothesis testing to interrogate analyze and interpret data effectively.

• Strong programming skills includingproficiencyin Python and experience with computer vision and machine learning frameworks such as TensorFlowKeras andPyTorch.

• Familiarity with software development best practices including CI/CD pipelines containerization such as Docker and orchestration such as Kubernetes.

• Deep understanding ofMLOpspractices including model versioning A/B testing and continuous deployment.

• Deep understanding of cloud computing platforms such as Azure AWS or GCP distributed systems and large-scale data processing technologies such as Spark and Kafka.

• Proven experience leading computer vision and machine learning projects managing stakeholders and scaling computer vision and machine learning solutions in production environments.

• Excellent communication skills with the ability to present complex technical topics to both technical and non-technical audiences.

• Exceptional problem-solving and analytical skills with a focus on practical business-oriented outcomes.