--- title: 'Machine Learning Applied Scientist (Co-op) at Apera AI Inc' canonical: 'https://feeny.ai/job/machine-learning-applied-scientist-co-op-apera-ai-inc-vancouver-8pcx1f86nag6' type: 'job' last_seen: '2026-09-16' --- # Machine Learning Applied Scientist (Co-op) at Apera AI Inc - **Company:** Apera AI Inc - **Location:** Vancouver, Canada - **Posted:** 2026-09-15 - **Last confirmed live:** 2026-09-16 - **Apply:** https://job-boards.greenhouse.io/aperaaiinc/jobs/5239440007 ## Job description Apera is an innovative, Vancouver-based company at the forefront of robotics, AI, and machine vision — recognized with the 2025 Frost & Sullivan Technology Innovation Leadership Award and the 2024 BC Tech "Company of the Year, Growth" award. We're on a mission to redefine AI-driven robotic vision. Apera AI helps manufacturers make their factories more flexible and productive. Robots enhanced with Apera's software have 4D Vision — the ability to see and grasp objects with human-like capability. Challenging applications such as bin picking, sorting, packaging, and assembly are now open to fast, precise, and reliable automation. We work with the world's leading automotive OEMs and Tier 1 suppliers. Our portfolio spans Vue (our 4D Vision software), Forge (a no-code simulation and AI training studio where customers build, validate, and de-risk robotic cells before any hardware is bought), and VuePod, our new turnkey, productized bin-picking cell. ## Role Overview Apera AI is seeking a Machine Learning Applied Scientist (Co-op) for the 8 months term period (Jan 2027 - August 2027) to support the development of our 4D Vision Technology used by industrial robots to perform fast, precise tasks in manufacturing environments. This role is based in-person at our Vancouver office. In this role, you will apply machine learning and computer vision techniques to real-world challenges like robotic part picking and localization in structured, high-speed applications. You’ll prototype, evaluate, and improve models that are deployed on factory floors in industries such as automotive and industrial manufacturing. Employee Value Proposition (EVP) - Purpose : You’ll contribute to the intelligence behind robotic systems that perform precise, high-speed automation tasks such as part picking and placement for stamped metal components or machined assemblies. - Growth: You’ll gain hands-on experience applying academic concepts to production workflows and working with internal datasets, building robust models, and learning from system behavior in real deployments. - Motivators: You’ll be part of a collaborative, fast-moving team, and see your models tested in simulation and on real industrial robots used in customer-facing solutions. Major Objectives - Prototype and Evaluate Vision Models Within the first 90 days, implement machine learning models for object detection, depth estimation, or 6-DoF pose estimation. Benchmark performance using internal datasets that reflect real manufacturing conditions. [Tools: PyTorch, internal GPU cluster, dataset tools] - Translate Research into Production-Relevant Improvements Identify and prototype methods from recent ML or computer vision research. Adapt them to our application domain and evaluate them against production baselines. Document findings and trade-offs. [Focus: Model speed, stability, accuracy under varying lighting and part geometry] - Enhance Synthetic Data Generation for Model Training Contribute improvements to the synthetic data generation pipeline, focusing on expanding variation in object shape, material, and pose. Help ensure the dataset supports model generalization across production use cases. Critical Subtasks - Evaluate the ML Development Environment In your first month, review the current training and validation tools. Identify areas for performance or usability improvements and contribute one concrete change by mid-term. - Collaborate Cross-Functionally and Debug Model Issues Work with robotics and software engineers to understand deployment requirements and constraints. Assist in diagnosing issues with model performance observed during robotic testing or simulation, and help implement fixes or improvements. - Own and Deliver a Scoped ML Project Lead a focused initiative such as testing a new augmentation strategy, developing a lightweight evaluation tool, or experimenting with model modifications for improved robustness. Present outcomes with metrics and insights at the end of the term. - Support Research on a Strategic Vision Problem Join early investigations into longer-term capabilities, such as handling part occlusion or improving model behavior with similar-looking parts. Conduct benchmarking and literature review to inform future roadmap decisions. Culture and Situation Fit You’ll thrive if you value initiative, technical depth, and seeing data as a design lever, not just input. Apera AI is fast-paced, collaborative, and impact-driven. Engineers here build systems that make AI dependable in messy, real-world conditions You’ll thrive here if you: - Want to apply ML to real-world problems in industrial automation. - Are excited to see your work influence how robotic systems are built and deployed. - Enjoy solving practical problems with research-informed tools. ## Qualifications - Proficiency in Python and machine learning frameworks (e.g., PyTorch). - Understanding of computer vision fundamentals (e.g., detection, segmentation, 3D geometry). - Familiarity with model training, tuning, and evaluation workflows. - Interest in robotics or applying ML in production-grade software. Bonus Experience (Not Required) - Experience with synthetic data generation or tools like Blender. - Exposure to 6-DoF pose estimation, point cloud processing, or depth sensing. - Experience working in Linux or Docker-based environments. - Familiarity with AWS services used in ML development workflows (e.g., S3, EC2, SageMaker). The compensation for this co-op role is CAD $3,600 to $4,500 per month. This is your opportunity to gain hands-on learning experience in one of the fastest-growing industries at the intersection of robotics, AI, and industrial automation. Note: Please ensure you upload both your resume and transcript, either combined into a single file or as separate files. ## About Apera AI Inc ## Company Overview - **One-liner**: Apera AI develops 4D Vision technology that uses proprietary AI and machine learning to power object recognition, robotic pose estimation, and path planning for industrial automation. - **Entity Type**: Private, venture capital funded - **Headquarters**: Vancouver, British Columbia, Canada (Gastown district) - **Founded**: Year not publicly disclosed - **Founders**: Sina Afrooze (CEO) and Armin Khatoonabadi ## Core Business - Primary industry: Industrial robotics automation, AI/ML/DL, and advanced manufacturing - Target customers: B2B, Enterprise — world’s leading automotive manufacturers, Tier 1 suppliers, and other major manufacturing brands - Mission or purpose: To transform robotic automation with best-in-class 4D Vision, making manufacturing more reliable and productive through AI-powered vision guidance ## Products & Services - **4D Vision Technology**: Proprietary AI-powered technology that controls object recognition, robotic pose estimation, and path planning. Gives robots faster decision-making and resilience to changes in lighting conditions. - **Apera Vue Robotic Vision Software**: Complete robotic guidance software that is robot-agnostic and compatible with leading robot brands. Runs 4D Vision through robotic workcells. - **Apera Forge (Forge Lab)**: AI-powered robotic vision training portal and simulation environment that helps customers prove out applications and gain certainty of ROI before deployment. **Applications served**: Assembly, Robotic Bin Picking, Sorting, Packaging & Kitting, Machine Tending ## Market Standing - **Valuation**: Not publicly disclosed - **Key Metric**: Private company; funding details not publicly disclosed - **Notable Investors/Partners**: Not publicly listed; company describes itself as "venture capital funded" - **Growth Signals**: Experiencing rapid growth in a large, global addressable market; actively hiring across multiple roles (Senior Accountant, Senior ML/CV Applied Scientist, Marketing, Sales, Business Development); customers include world’s top automotive manufacturers and Tier 1 suppliers ## Competitive Advantages - **4D Vision technology**: Proprietary AI that delivers exceptional speed and accuracy (reported ~99% accuracy) with resilience to varying lighting conditions — a key differentiator from traditional vision systems - **Robot-agnostic software**: Vue works with leading robot brands, reducing lock-in risk for customers - **Simulation-first approach**: Forge Lab reduces deployment risk and increases customer confidence in ROI - **Deep technical team**: Founders and engineers come from high-growth companies like Avigilon (sold for $1.2B to Motorola) and Amazon Web Services (AWS) - **10+ patents** held by the founding team in AI, digital imaging, image processing, and media streaming ## Strategic Focus - Expanding globally with a dedicated sales team across North America (Detroit, Alabama, South Carolina) and LATAM (Mexico) - Scaling marketing and demand generation to drive adoption in automotive and industrial manufacturing - Continuing to advance 4D Vision technology and simulation capabilities to reduce barriers to automation adoption - Targeting labor shortage challenges in manufacturing with vision-guided robotics solutions ## Why Work Here - **Culture**: Highly technical engineering environment at the intersection of manufacturing and AI/ML/DL. The team collaborates closely and is close to customer needs with a clear roadmap. Values include continuous learning, problem-solving, and rewarding ability with growth opportunities. - **Impact**: Employees can affect the path of the company and see their work implemented by the world’s leading manufacturers. - **Compensation & Benefits**: - Generous stock option package - Competitive compensation - Comprehensive health, dental, and life insurance - 3 weeks paid vacation - Flexible working hours and work from home options - Great Vancouver location in Gastown, close to public transit - **Team**: Strong engineering team working on robotics, 3D math, simulation, computer vision, deep learning, software engineering, cloud computing, and UI. Described as a “technically rich environment” where work crosses boundaries. - **Diversity**: Welcomes people of all ages, genders, religions, ethnicities, and abilities. ## Sources 1. [apera.ai](https://apera.ai/about-apera-ai/) 2. [apera.ai](https://apera.ai/) 3. [apera.ai](https://apera.ai/careers/) 4. [greenhouse.io](https://job-boards.greenhouse.io/aperaaiinc) 5. [apera.ai](https://apera.ai/about-apera-ai/leadership/) ## Other roles at Apera AI Inc - [Software Developer - C++ (Co-op)](https://feeny.ai/job/software-developer-c-co-op-apera-ai-inc-vancouver-aeq4yz7a5syc) — Vancouver, Canada - [Sr. Software Engineer, Cloud Platform](https://feeny.ai/job/sr-software-engineer-cloud-platform-apera-ai-inc-vancouver-yn485tggfvtx) — Vancouver, Canada - [Field Application Engineer](https://feeny.ai/job/field-application-engineer-apera-ai-inc-germany-tx3bjv30z2rs) — Germany - [Growth & Digital Marketing Manager](https://feeny.ai/job/growth-digital-marketing-manager-apera-ai-inc-mexico-fr2ybxrs3h1g) — Mexico - [Brand, Content & Application Media Producer](https://feeny.ai/job/brand-content-application-media-producer-apera-ai-inc-mexico-enysdhk71mf5) — Mexico - [Senior Product Manager](https://feeny.ai/job/senior-product-manager-apera-ai-inc-remote-gyvcgnd8hvv8) - [Senior Business Development Manager](https://feeny.ai/job/senior-business-development-manager-apera-ai-inc-michigan-4dvgc5spfpsv) — Michigan - [Software Development Engineer – Platform](https://feeny.ai/job/software-development-engineer-platform-apera-ai-inc-vancouver-f5nzyt1hnm22) — Vancouver, Canada - [Roboticist – (Co-Op)](https://feeny.ai/job/roboticist-co-op-apera-ai-inc-vancouver-ez9fk9yjg7ex) — Vancouver, Canada - [Software Developer - C++ (Co-op)](https://feeny.ai/job/software-developer-c-co-op-apera-ai-inc-vancouver-m6ms8wyva5ae) — Vancouver, Canada