Everseen – AI/ML Engineer I

Job Description

Everseen is hiring an AI/ML Engineer I in Pune to design, develop, optimize, and deploy artificial intelligence and machine learning solutions for real-world business applications. This opportunity is particularly suited to engineers with a strong interest in computer vision, deep learning, model optimization, and production machine learning systems. The selected candidate will work on AI/ML components that contribute directly to Everseen's vision AI products and help global retailers improve operational efficiency, reduce retail shrink, and enhance customer experiences. The role goes beyond experimentation because engineers are expected to take ownership of important machine learning features and turn research concepts into efficient, reliable, production-ready solutions. Candidates will work with technologies including Python, C/C++, CUDA, PyTorch, OpenCV, TensorFlow, TensorRT, and ONNX while developing solutions capable of handling demanding computer vision and real-time video processing workloads.

The AI/ML Engineer I will participate in the complete model development lifecycle, beginning with experimentation and algorithm development and continuing through optimization, deployment, and production maintenance. Engineers will design experiments, analyze datasets and results, tune machine learning models, compare different approaches, and clearly communicate their findings through presentations and technical documentation. A key expectation is the ability to take ideas described in research papers and convert them into working algorithms or engineering solutions. The role also requires an understanding of the practical challenges involved in moving machine learning models from research environments into production, including inference latency, scalability, computational efficiency, reliability, and maintainability. Experience with technologies such as TensorRT and ONNX can be particularly valuable for optimizing inference performance, while CUDA knowledge can help engineers work effectively with GPU-accelerated workloads. Candidates will also contribute to reproducible ML pipelines and workflows that make experimentation and production delivery more consistent.

Everseen operates computer vision technology at significant global scale, making this role an opportunity to work with challenging AI systems rather than purely theoretical machine learning problems. The company processes large volumes of retail video data and supports computer vision solutions across thousands of stores and checkouts. Engineers in this position will collaborate with research scientists, AI specialists, software engineers, and other cross-functional teams to develop solutions that can operate reliably in real-world environments. The technology environment includes Linux, Docker, Kubernetes, Git, CI/CD pipelines, real-time video processing, RTSP/video streaming, and cloud platforms. The ideal candidate is an analytical problem solver who can work independently, understand how technical components influence business outcomes, and continuously improve model quality and production efficiency. This position is well suited to professionals looking to build a career in AI engineering, machine learning, computer vision, deep learning, and production-scale model deployment.

Roles & Responsibilities

1. Own ML Components
   Take independent ownership of assigned machine learning components and features, ensuring that they are designed, implemented, tested, optimized, and delivered according to project requirements.
2. Develop AI/ML Solutions
   Design and implement machine learning and computer vision algorithms that address practical business and product requirements while meeting performance and reliability expectations.
3. Conduct ML Experiments
   Design controlled experiments, establish appropriate evaluation methods, analyze results, and use evidence from experiments to determine the most effective technical approach.
4. Optimize Model Performance
   Improve model accuracy, inference speed, computational efficiency, scalability, and resource utilization for production environments and real-time workloads.
5. Implement Research Algorithms
   Study relevant research papers and independently translate published approaches into practical algorithms, prototypes, and production-oriented machine learning solutions.
6. Move Models Into Production
   Transform research and experimental models into production-ready systems while considering latency, scalability, reliability, maintainability, and operational requirements.
7. Build Reproducible Pipelines
   Create reliable and repeatable ML workflows that support experimentation, model training, evaluation, validation, deployment, and future research.
8. Work With Computer Vision Systems
   Develop and improve computer vision solutions using frameworks and libraries such as PyTorch, OpenCV, TensorFlow, ONNX, and TensorRT.
9. Support Real-Time Video Processing
   Work with real-time video streams and technologies such as RTSP to develop AI solutions capable of processing video efficiently in operational environments.
10. Develop GPU-Accelerated Solutions
    Use CUDA and related technologies where appropriate to improve the performance of computationally intensive machine learning and computer vision workloads.
11. Collaborate Across Teams
    Work closely with research, engineering, product, and other cross-functional teams to align technical solutions with project requirements and business outcomes.
12. Document and Present Findings
    Prepare clear technical documentation and research reports while presenting experimental results, conclusions, and recommended design solutions to relevant stakeholders.

Requirements & Eligibility

1. Relevant Professional Experience
   Candidates should have approximately 1–3 years of experience in AI/ML engineering, machine learning, computer vision, data science, or a closely related technical position.
2. Educational Qualification
   A Bachelor's or Master's degree in Engineering, Computer Science, Machine Learning, Artificial Intelligence, or a related technical field is preferred.
3. Machine Learning Fundamentals
   Strong understanding of machine learning algorithms, model training, hyperparameter tuning, evaluation methodologies, and the practical considerations involved in selecting an appropriate model.
4. Deep Learning Experience
   Candidates should have practical experience with deep learning concepts and at least one major framework such as PyTorch or TensorFlow.
5. Computer Vision Knowledge
   Understanding of computer vision concepts and experience with tools such as OpenCV will be valuable for working on Everseen's vision AI products.
6. Strong Programming Skills
   Good programming ability in Python is essential. Experience with C or C++ is advantageous, particularly for performance-sensitive AI applications.
7. Model Optimization
   Candidates should understand how to improve model inference performance and should be familiar with practical concerns such as latency, scalability, memory consumption, and computational efficiency.
8. Research Implementation Skills
   The ability to understand technical research papers and independently implement the algorithms or methodologies described in them is important for this position.
9. Analytical & Statistical Thinking
   Strong analytical ability, data interpretation, statistical reasoning, and the capacity to identify trends and make evidence-based technical decisions are expected.
10. Problem-Solving & Ownership
    Candidates should demonstrate practical problem-solving skills, independent decision-making, attention to code and model quality, and the ability to take ownership of complex technical work.

Technical Skills

• Python
• C/C++
• CUDA
• PyTorch
• TensorFlow
• OpenCV
• TensorRT
• ONNX
• Linux
• Docker
• Kubernetes
• Git
• CI/CD
• Computer Vision
• Deep Learning
• Machine Learning
• Real-Time Video Processing
• RTSP / Video Streaming
• Cloud Platforms
• Model Optimization
• ML Pipelines

Expected Salary

For an AI/ML Engineer I position in Pune requiring approximately 1–3 years of experience, a reasonable market expectation is around ₹8 lakh to ₹15 lakh per year, depending on specialization and overall technical expertise. Candidates with strong computer vision, deep learning, CUDA, TensorRT, model optimization, and production deployment experience may command compensation toward the higher end of the range. The actual salary offered by Everseen can vary based on experience, technical assessment performance, role level, and the company's compensation structure.

Why Consider This Opportunity?

The Everseen AI/ML Engineer I position provides an opportunity to work on production-grade computer vision and vision AI systems rather than limiting machine learning work to research notebooks or experimental prototypes. Engineers can contribute to technology designed for major global retailers and work on problems involving real-time video, large-scale data processing, model optimization, and operational reliability.

The role is also technically broad. Professionals can strengthen their experience across PyTorch, TensorFlow, OpenCV, TensorRT, ONNX, CUDA, Docker, Kubernetes, cloud platforms, and CI/CD, while developing a deeper understanding of how machine learning models are taken from research concepts into production systems. This combination of AI research implementation and software engineering can be valuable for engineers who want to progress toward senior machine learning, computer vision, or AI infrastructure roles.

Everseen's engineering environment emphasizes ownership, collaboration, customer focus, speed, and continuous improvement. The company's global footprint and work with large retailers provide exposure to complex production environments where model quality and system performance have a direct business impact. For professionals passionate about computer vision, deep learning, AI engineering, and real-time machine learning, this Pune opportunity offers strong technical exposure and meaningful product challenges.

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