Spexi

Senior Machine Learning Engineer

Spexi

24 days ago

## Senior Machine Learning Engineer at Spexi **Spexi** is a drone technology company on a mission to make ultra-high-resolution geospatial imagery more accessible than ever before, empowering humanity to make better decisions about the physical world. We're building an exciting new two-sided marketplace called the Spexi Network, powered by drones and blockchain technology. It's the world's first Fly-to-Earn platform that enables drone pilots to earn rewards for flying and collecting aerial imagery. It also enables organizations of all sizes to quickly and easily access high-resolution aerial imagery and valuable derivative data, powering remote monitoring of buildings, infrastructure, natural resources, and more. Our goal is to guide their decision-making and help them better plan and react, without needing to own drones or hire pilots. We're looking for a **Senior Machine Learning Engineer** to lead the development of experimental models, algorithms, and prototype systems that push the boundaries of what's possible with geospatial imagery analytics. Your work will bridge early-stage research and production—delivering high-quality, well-structured code that serves as a foundation for the next generation of Spexi's geospatial intelligence products. ### Responsibilities - Design, train, and productionize models for **aerial-image classification**, **object detection**, and **2D/3D segmentation** across diverse geographies, sensors, resolutions, and seasons. - Spearhead the integration and optimization of state-of-the-art **foundation models** for aerial segmentation, adapting **SAM2**-like capabilities and subsequent architectures through prompt engineering, fine-tuning, and distillation. - Engineer **change detection** and structure-change models capable of distinguishing real-world physical changes from acquisition noise and seasonal lighting variations. - Develop **predictive models** for trend forecasting, integrating time-series methods with spatial context to monitor vegetation growth, construction, and asset degradation. - Build **Generative AI** capabilities, including **multimodal models** and natural-language query systems that ground language in georeferenced pixels and semantic layers. - Design and operate scalable **ML pipelines on AWS**, leveraging **SageMaker**, S3, and Step Functions to move from research prototypes to production endpoints. - Track the frontier of research—including **NeRFs**, **Gaussian Splatting**, and **diffusion models**—translating relevant breakthroughs into shipped product capabilities. - Collaborate with photogrammetry and platform teams to ensure ML outputs maintain **geospatial accuracy** and align to coordinate reference systems. - Establish rigorous **evaluation benchmarks** and metrics to validate model performance under real-world production conditions. ### What You Bring #### Minimum Qualifications - An **M.S. and 5+ years** of work experience in Computer Science, Computer Vision, Machine Learning, Remote Sensing, or a related quantitative field. - Proven experience in **research-to-production translation**: acting as the bridge between pure academia and commercial engineering—demonstrating the ability to read a newly published research paper, replicate its findings, rapidly prototype, and distill it into a production-ready feature. - At least 3 years of **applied ML and computer vision** experience transitioning models from research to production, ideally involving **geospatial**, aerial, or satellite imagery. - Deep, contemporary expertise in **predictive AI** for imagery, including **classification**, **object detection**, and **segmentation**, with a strong technical perspective on the efficacy of modern feature-extraction methods. - Working knowledge of **SAM2** or similar algorithms—including fine-tuning, prompt design, and distillation—and a clear understanding of its strengths and failure modes within the context of aerial datasets. - Hands-on experience developing **Generative AI** capabilities, such as **multimodal RAG**, vision-language models, and diffusion-based pipelines, with the ability to ship complete systems end-to-end. - Strong technical judgment regarding the selection of **predictive vs. generative** approaches, considering critical factors like cost, latency, and evaluability. - Production experience operating **ML pipelines on AWS**, specifically utilizing **SageMaker** for training and hosting, alongside broader AWS data orchestration services. - Experience managing large, complex imagery datasets in cloud environments while optimizing models for real-world performance, throughput, and cost-efficiency. #### Preferred Qualifications - A **Ph.D. and 7+ years** of work experience blending artificial intelligence with the physical sciences (e.g., Photogrammetry, Physics). - Deep expertise in **geospatial and remote sensing** workflows, including hands-on experience with **georeferenced imagery**, coordinate reference systems, projections, and industry-standard tools like **GDAL**, **PostGIS**, and **rasterio**. - Proven ability to adapt or pretrain **geospatial foundation models** to specialized remote-sensing tasks. - Specialized experience in **3D scene understanding**, leveraging **NeRFs**, **Gaussian Splatting**, and point cloud segmentation to ensure multi-view consistency across 2D and 3D ML outputs. - Architectural experience designing **multimodal RAG systems** that integrate imagery, vector, and time-series data, with a focus on rigorous retrieval and generation benchmarks. - Background in **fast-paced startup environments**, with a demonstrated capability to translate experimental research into production-quality geospatial intelligence systems. ### Benefits & Perks At Spexi, we believe that a solid work-life balance is crucial for producing the best products for our customers. To help our employees stay happy and healthy, we offer the following benefits and perks: - Remote-friendly environment (with a hub in Vancouver, Canada) - Flexible hours - Medical, dental, and vision health benefits Spexi is an inclusive employer that values workplace equality, supports diversity, and respects the unique qualities each individual brings to the company. We thank all applicants for their interest. All applications will be reviewed to determine which candidates' education and experience best meet the needs of the position. Only individuals selected for interviews will be contacted. *When applying, mention the word CANDYSHOP to show you read the job post completely.*

Mid-Market Account Executive

Spexi

150 days ago

## Mid-Market Account Executive **About Spexi:** At Spexi, we’re revolutionizing accessibility to high resolution geospatial imagery through cutting edge drone technology. We’re on a mission to empower individuals and businesses alike with unprecedented spatial insights. We are building the world’s most accessible high resolution geospatial network, democratizing data once reserved for the largest enterprises and putting powerful insights into the hands of decision makers everywhere. **The Role:** As a Mid-Market Account Executive, you will be responsible for driving new business acquisition and expanding accounts within the commercial and mid-market segments. You will own the full sales cycle from prospecting to close, converting interest into adoption and turning customers into advocates. While our Enterprise team focuses on large, complex strategic deals, this role is focused on velocity and precision. You will manage a higher volume of opportunities, drive shorter sales cycles, and aggressively capture market share in key verticals like Insurance, Real Estate, Construction, and Technology. This role requires strong pipeline management, accurate forecasting, and consistent quota attainment. **Location:** This position is primarily remote. However, you will occasionally be required to travel to our office in the 800 block of Powell Street, Vancouver BC to foster collaboration and engage in strategic planning sessions. * **Employment Type:** Full time * **Department:** Sales **Why Join Now?** You are joining at the perfect inflection point. We have product-market fit, a massive addressable market, and we need a Mid-Market engine to capture it. If you want to sell a product that feels like the future, build a lucrative territory from the ground up, and accelerate your career in a high-growth tech environment, this is the seat for you. **About You:** You are a high-energy sales professional who thrives on momentum. You don’t just wait for leads; you hunt for them. You are organized, process-driven, and capable of juggling multiple deals without dropping the ball. - **Velocity Mindset:** You understand how to move deals forward quickly. You don’t let opportunities stagnate. - **Coachability:** You are eager to learn, adapt to new methodologies, and refine your craft based on data and feedback. - **Curious Hunter:** You are relentless in outbound prospecting, finding creative ways to engage Directors and VPs at target companies. - **Process Oriented:** You treat your CRM as your source of truth, keeping your pipeline clean and your forecasting accurate. **Responsibilities:** - **Accelerate Revenue Growth:** Drive new business acquisition and expansion in the mid-market segment. Consistently meet or exceed monthly and quarterly quotas through a mix of outbound prospecting and inbound lead conversion. - **Manage Full-Cycle Sales:** Own the process from initial outreach and discovery to demo, negotiation, and close. - **Pipeline Mastery:** Maintain a healthy pipeline of 3 to 4 times coverage. Accurately forecast revenue, and manage a high volume of active deals simultaneously. - **High-Volume Prospecting:** Execute targeted outbound campaigns and outreach to key decision-makers to consistently generate qualified opportunities in target industries. - **Solution Selling:** Conduct discovery calls to uncover deep-seated pain points and clearly articulate how Spexi’s geospatial data solves specific operational challenges. - **Collaborate:** Work closely with Product and Marketing to refine messaging and share feedback from the front lines. **What You Bring:** - **Proven Sales Experience:** **3 to 5 years** of B2B SaaS sales experience (closing role), with a track record of consistently hitting or exceeding quota. - **Deal Mechanics:** Experience managing deal sizes ranging from **$10k to $80k ARR** with sales cycles of 30 to 90 days. - **Geospatial Interest:** Experience in the Geospatial/Drone industry is a massive plus, but a strong technical aptitude and desire to learn is required. - **Communication Skills:** Ability to break down complex technical concepts into simple, value-based business arguments. - **Methodology:** Familiarity with sales methodologies (e.g., MEDDPICC, SPICED, or Sandler) and the discipline to apply them to deal qualification. - **Tech Stack:** Proficiency with CRM tools (HubSpot/Salesforce), sales engagement platforms, and Google Meet. **Benefits and Perks:** Joining Spexi means being part of a supportive and dynamic team. Here’s what we offer: - Friendly, casual environment that fosters collaboration and creativity. - Flexible hours to help maintain a healthy work-life balance. - A generous vacation policy that allows you to recharge and rejuvenate. - Medical, dental, and vision health benefits. - Continuous professional development opportunities to advance your career. - Inclusive workplace culture that values diversity and individual contributions. **Compensation:** Base salary of $85,000 to $105,000, plus commission, with on-target earnings of $160,000 to $180,000. We will tailor the offer within these ranges based on experience. Spexi believes that promoting innovation and creativity requires an environment where employees feel supported and valued. We are committed to providing a positive and inclusive work environment where everyone can thrive and contribute to our mission. Spexi is an equal opportunity employer and does not discriminate based on race, ethnicity, religion, sex, gender identity or expression, sexual orientation, age, disability, national origin, or any other protected status. We thank all applicants for their interest. All applications will be reviewed to determine which candidates' education and experience best meets the needs of the position. Only individuals selected for an interview will be contacted. When applying, mention the word **CANDYSHOP** to show you read the job post completely.