Entry level machine learning engineer serp_jobs.h1.location_city

About Us :

EyePop.ai is a fast-growing AI startup on a mission to make powerful Visual AI accessible to everyone. Based in San Diego, we’re building cutting-edge computer vision tools that help teams unlock insights from their visual data.

We’re already collaborating with industry leaders like Qualcomm and other major players in the San Diego tech ecosystem to push the boundaries of what’s possible with AI. Whether it’s real-time image analysis, smart data workflows, or seamless model deployment, we’re making it happen — and fast.

At EyePop, you’ll be part of a close-knit, high-impact team shaping the future of AI-powered applications in a vibrant, hands-on environment.

Job Description :

We’re looking for a Machine Learning Software Engineer to join us at an exciting stage in our startup journey. As part of our small, fast-moving team, you’ll play a hands-on role in shaping both our technology and our company. You’ll split your time between building cutting-edge models for Visual AI and Computer Vision applications and developing the software systems that bring them to life in production.

Whether you’re crafting our ultra-optimized, single-purpose models or pushing the limits with our general-purpose generative and agentic AI solutions, your work will shape our product and deliver real impact for our customers. Every model you build and every system you deploy will drive meaningful results — in the hands of users.

This is a rare opportunity to work side by side with product, business, and technical leaders—building not just models, but the future of our platform. You’ll also be working alongside experienced founders who've had multiple exits and are industry veterans. If you thrive in a fast-paced, high-ownership environment where your work directly drives the success of the company, we want to meet you.

Responsibilities :

• Design, build, and assess cutting-edge machine learning models for diverse computer vision and visual AI applications, spanning object detection, segmentation, and transformative generative vision language models (VLMs).
• Drive innovation in the development and evaluation of Agentic Visual Intelligence workflows.
• Partner with fellow ML / AI engineers and key stakeholders to sculpt groundbreaking software solutions leveraging state-of-the-art artificial intelligence and machine learning techniques.
• Craft robust, maintainable software to power seamless model training, evaluation, and deployment workflows.
• Revolutionize and enhance our data pipelines and model training infrastructure to accelerate iterative experimentation.
• Optimize and package models for deployment, guaranteeing peak performance, scalability, and observability in production environments.
• Team up with experienced engineers to flawlessly integrate models into customer-facing SDKs and APIs.
• Elevate our collective expertise through impactful code reviews, dynamic design discussions, and the establishment of superior technical standards.
• Required
• Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 2+ years experience developing / deploying ML models, data science pipelines, and computer vision solutions.
• 2+ years experience building software for ML / data science workloads.
• Experience with TensorFlow, PyTorch, Keras, or similar frameworks.
• Experience with pandas and Python scientific computing libraries
• Strong Python programming skills.
• Proficient in software development best practices (e.g., test-driven development) and Git.
• Strong analytical and problem-solving skills.
• Thrive in a fast-paced, high-intensity environment where the team moves quickly, tackles tough challenges, and isn’t afraid to put in extra time to drive real, exciting results.
• Comfortable navigating ambiguity, handling pressure, and staying focused in the face of shifting priorities.
• Excellent communication and teamwork skills.
• Desired
• Experience with generative and agentic AI (VLMs, LLMs, Vector DBs).
• Experience with CV / ML deployment libraries (Gstreamer, ONNX, TorchScript, TensorRT).
• Demonstrated experience with hardware acceleration (GPUs, TPUs) for ML / data science optimization.
• Understanding in fundamentals of linear algebra, probability and statistics.

What We Offer :