**What You'll Do** You'll design and deliver machine learning solutions that blend cutting\-edge research with practical deployment. Working across industries and use cases, you'll tackle challenging problems in computer vision and build robust models that power client\-facing tools and internal platforms. * Develop End\-to\-End CV Models: Design, train, and evaluate deep learning models (e.g., YOLO, optical flow, ResNet architectures) tailored to complex visual data pipelines and novel problem domains. * Collaborate on Real\-World Solutions: Partner with software engineers and fellow data scientists to integrate research\-driven models into deployable systems that operate in dynamic production environments. * Client\-Focused Problem Solving: Work closely with external stakeholders to frame ambiguous problems, explore solution paths, and translate technical insights into impactful results. * Explore, Iterate, Validate: Lead the exploration and analysis of large datasets using tools like Pandas, NumPy, and Spark to inform model design and evaluate performance under realistic constraints. * Research\-Driven Innovation: Identify when state\-of\-the\-art ideas can be adapted and productionized in service of the problem at hand. **What We Need** Professional Experience: * 2\+ years of hands\-on experience building computer vision models using modern deep learning techniques. * Proven ability to take models from prototype to production in Python\-based workflows. * Experience working in client\-facing roles or directly engaging with stakeholders to refine project requirements. Technical Expertise: * Strong proficiency in Python and commonly used ML/data libraries (Pandas, NumPy, PyTorch, etc). * Familiarity with core computer vision tools and model types (YOLO, ResNet, segmentation models, optical flow, etc). * Experience working with large\-scale datasets using distributed tools such as Spark. * Comfort navigating cloud environments (GCP, AWS, or similar); Databricks experience is a plus. * Solid grasp of experimental design, model evaluation, and data debugging practices. * Strong code hygiene: able to write clean, modular, testable code in collaborative environments. Bonus (Nice to Haves): * Familiarity with MLOps practices (model tracking, versioning, reproducibility). * Experience contributing to multi\-model systems or pipelines built by larger teams of data scientists and engineers. We offer a pay range of $30\+ per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you'll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply. **Important:** All candidates must pass an interview as part of the contracting process.