• Develop and improve computer vision models for sports video, including player and ball detection, tracking, event recognition, and identity association. • Build and improve camera calibration, homography, and field-registration solutions that map image coordinates into normalized field coordinates. • Analyze existing computer vision pipelines, establish baselines, identify weak links, and recommend practical improvements. • Improve tracking robustness across different stadiums, camera placements, broadcast styles, video qualities, and environmental conditions. • Design experiments covering data acquisition, dataset creation, augmentation, model training, fine-tuning, evaluation, and deployment readiness. • Analyze failure modes and implement improvements that increase accuracy, reliability, scalability, and robustness. • Adapt existing models and pipelines to support new sports, leagues, camera configurations, and video sources. • Partner with data teams on labeling workflows, dataset quality, validation processes, and human-in-the-loop improvement cycles. • Work closely with software, platform, and DevOps engineers to deploy computer vision models and pipelines into production environments. • Improve inference performance, scalability, monitoring, and operational reliability. • Establish evaluation metrics, testing processes, and quality controls to ensure model performance remains consistent over time. • Lead initiatives end-to-end, from early technical discovery and prototyping through production deployment and ongoing improvement. • Contribute to system design decisions that integrate computer vision, machine learning, backend services, operations, and client workflows. • Communicate technical tradeoffs clearly with internal teams, client stakeholders, and engineering leadership.

• You will develop a next-generation localization product with a learned map architecture. • You will design and implement visual and acoustic sensor systems for drone detection. • You will develop a multi-sensor perception and fusion system for the drone early-warning system. • You will run machine learning and AI models directly on local sensors rather than on cloud servers. • You will design, build, and maintain scalable models and bring model inference directly to drone-detection devices. • You will implement scalable, low-latency intelligence. • Together with the ML, MLOps, and DevOps teams, you will enable fast and secure deployments. • You will monitor systems, troubleshoot issues, and continuously improve observability. • If desired, you will support on-site operations, collect sensor data, and validate the technology in controlled field trials.

Role Description Comcast Business is scaling Computer Vision–powered solutions as part of the Advanced Technology Solutions portfolio. The “Sr. Director- Computer Vision Solutions” is a customer-facing technical sales leader responsible for owning funnel growth, solution design, technical credibility, sales results, and deployment success across enterprise customers for our Comcast Business Vision Intelligence and IoT portfolio. The primary responsibility is driving revenue growth. Customer-Facing Expertise - Lead technical discovery with enterprise customers to understand environments, workflows, constraints, customer needs/pain-points, and success criteria in order to build a robust funnel. - Design end-to-end Vision Intelligence solutions spanning cameras, sensors, networking, software, and integrations to move qualified opportunities through the funnel. - Drive revenue growth through winning enterprise opportunities in the funnel. - Collaborate tightly with the Comcast Business Enterprise sales organizations as an overlay sales team. Technical Leadership in Sales & Pre-Sales Motions - Serve as the lead Solutions Architect / Sales Engineer in complex customer engagements, collaborating closely with the product organization. - Support Sales teams through technical presentations, discovery and qualification, pricing/proposal delivery, and architecture security reviews. - Respond to technical RFP/RFI requirements and clearly articulate technical tradeoffs, risks, and feasibility. - Lead a team of technical sales facing direct reports. - Collaborate with the Product team to build and deliver on customer requirements. Pilot Execution & Field Enablement - Architect and guide field pilots including site readiness, hardware validation, and network assessments. - Partner with Product, Marketing, and Operations to troubleshoot and optimize real-world deployments. - Drive pilot-to-production transitions with clear technical recommendations and value. Product & Marketing Partnership - Act as the technical voice of the customer, translating field learnings into product and architecture feedback to Product and Marketing teams. - Collaborate tightly with the Marketing team to shape marketing campaigns, messaging, enterprise sales enablement tools, and provide technical and eco-system expertise. Qualifications - 5+ years in Vision Intelligence / Computer Vision enterprise sales roles. - 10+ years in enterprise technology ecosystem. - Deep technical experience with computer vision, video systems, IoT, and networking. - Proven ability to design and communicate complex systems to both technical and executive stakeholders. - Professional communication and executive presentation skills. - Hands-on experience supporting enterprise pilots and production deployments. - Sales leadership experience and proven large enterprise technical sales success. - Travel 50%. Requirements - Understand our Operating Principles; make them the guidelines for how you do your job. - Own the customer experience - think and act in ways that put our customers first. - Know your stuff - be enthusiastic learners, users and advocates of our technology. - Win as a team - make big things happen by working together. - Be an active part of the Net Promoter System. - Drive results and growth. - Support a culture of inclusion in how you work and lead. - Do what's right for each other, our customers, investors, and our communities. Benefits - Base pay within the posted range for this role, dependent on job-related, non-discriminatory factors such as experience. - Most sales positions are eligible for a Commission under the terms of an applicable plan. - Most non-sales positions are eligible for a Bonus. - Best-in-class Benefits to eligible employees. - Support for physical, financial, and emotional needs through various options and tools. Education - Bachelor's Degree preferred, or a combination of coursework and experience, or extensive related professional experience. Certifications - Relevant Work Experience: 10 Years + Company Description Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.

Role Description - Benchmark baseline model performance on a representative image sample. - Measure accuracy against a held-out set and assess data quality. - Evaluate the realistic performance ceiling of the computer vision system. - Translate findings into a decision-grade report for a non-technical executive audience. - Work independently and asynchronously to meet deadlines and improve AI model performance. Qualifications - Must-Have: 5+ years in computer vision and ML engineering. - Experience classifying or grading physical objects from images. - Strong evaluation discipline in representative sampling and accuracy benchmarking. - Ability to assess feasibility and communicate clearly to a non-technical audience. - Preferred: Experience with authentication, counterfeit, or anomaly detection. - Exposure to private equity diligence or time-boxed advisory work. - Familiarity with imaging hardware, capture pipelines, and edge or on-prem deployment. Requirements - Contract type: Hourly contractor. - Compensation: $135/hour. - Location: Remote. - Duration: 3–4 weeks. - Commitment: 20+ hours/week. Application Process - Upload resume. - AI interview based on your resume. - Submit form. Resources & Support - For details about the interview process and platform information, please check: here . - For any help or support, reach out to: support@mercor.com . - Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.