AI Research Engineer (Computer Vision & Imaging)

Hi,

Greetings !!

We/re are looking for someone who has Hands-on experience with CV/ML

The location for the same is Bangalore.

Requirements

• 11–14 years total experience
• Computer Vision – strong hands-on experience
• Object Detection – YOLO(Preferred), Faster R-CNN, SSD, etc.
• Image Processing – OpenCV, image enhancement, segmentation, feature extraction
• Machine Learning / Deep Learning – CNNs, model training, evaluation, optimization
• AI/ML – production-level AI solution development
• LLM / GenAI – practical exposure to LLMs, multimodal AI, RAG, VLMs, or GenAI
• Python – strong programming skills
• Model deployment – preferably TensorRT, ONNX, Docker, Kubernetes, cloud, or edge deployment
• Bangalore – candidate should be based in / willing to work from Bangalore

Preferred

• Vision Transformers / ViT
• YOLOv8/YOLOv9/YOLOv10/YOLO11
• PyTorch / TensorFlow
• NLP / LLM / VLM
• Generative AI
• CUDA / GPU optimization
• Edge AI / NVIDIA
• Experience leading CV/AI projects or teams

If interested, Share CV at: snigdhaattheratebeanhr.com

Position: Computer Vision Engineer

Experience: 2–3 Years

Location: Bengaluru, Karnataka

Employment Type: Full-time

About the Role

We are seeking a highly motivated Computer Vision Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating computer vision models and algorithms and pipelines for UAVs operating in both GNSS-available and GNSS-denied environments.

The ideal candidate should have a strong foundation in theory of deep learning and machine learning, strong understanding of electromagnetic spectrum, imaging fundamentals, camera principles, and mathematical concepts with hands-on experience in implementing these algorithms on embedded or real-time systems.

Key Responsibilities

• Design, develop, and optimise AI Models
• Make custom CNNs/ modify existing CNNs to suit specific problems at hand
• Handle end-to-end training flow
• Implement end to end inference pipelines on standard PCs as well as on embedded systems
• Understand performance benchmarks and assess the accuracy and inference times
• Implement traditional image processing algorithms
• Factor the code to leverage underlying hardware architecture
• Prune the networks for efficiency
• Integrate the system within the application framework using C++
• Work closely with perception, controls, embedded software, and systems engineering teams.

Required Qualifications

• B.E./B.Tech/M.E./M.Tech in Computer Science and Engineering, Electronics, ECE, Mechatronics, or a related discipline.
• 2–3 years of experience in relevant area
• Strong understanding of: Linear Algebra, Probability and Statistics, AI-ML-DL fundamentals, Image processing, Camera Functioning
• Strong programming skills in C++ and Python.
• Experience with MATLAB for algorithm development and validation.
• Familiarity with Linux development environments.
• Experience with Git version control.

Preferred Skills

• Experience with Camera, IMU Calibration and Synchronisation
• Experience with multi-sensor fusion.
• Experience working with NVIDIA devices
• Experience on FPGA will be an added advantage
• Full understanding of Git functionality
• Exposure to airborne software development processes and coding standards (e.g., MISRA C++).

Personal Attributes

• Strong analytical and problem-solving skills.
• Ability to work independently on challenging technical problems.
• Good communication and documentation skills.
• Passion for solving challenging problems
• Willingness to participate in field trials and flight testing.
• Team player

About the role

We give you a product design and a brief. You turn it into backend software that analyses images and user input and hands our frontend team the structured data it needs.

Most of the code gets written by AI agents like Claude Code and Codex, with you directing them. That makes you responsible for every line they produce, including the wrong ones. Your value is knowing what to ask for and catching what the agent got wrong. If “the AI did it” sounds like a reasonable defence to you, this job will frustrate you.

What you will do

1. Read a design and work out what data each part of it needs.
2. Build the backend logic that produces that data, with AI coding agents doing most of the typing.
3. Set up open-source computer vision and AI models, run them on real images, and decide whether they are good enough.
4. Check your own output before anyone reviews it. Wrong values, invented APIs and messy code should stop with you.
5. Ship small, well-typed pull requests that get through code review.

You won’t have to come up with the product itself. We do that part, and your job is to make it work and keep it maintainable.

You will fit if you

1. Write clear, precise English in prompts, pull requests and messages. This is the first thing we screen for.
2. Use Claude Code, Codex or Cursor every day, and can show us how you break a task down for an agent.
3. Know enough computer vision, machine learning and data engineering to ask for the right thing and to recognise a wrong answer when you see one.
4. Are a solid Python engineer who understands typing and async, and who spots bad patterns in a diff quickly.
5. Look at the actual output every time. Code that runs proves very little.

Nice to have

1. Experience with OpenCV or similar image libraries.
2. Experience with FastAPI, workflow engines, or cloud storage.
3. Experience getting structured outputs from LLM APIs.
4. A side project where you got an open-source model running and evaluated it.

How to apply

Send your CV and answers to these 3 questions, 150 words maximum each:

1. Describe one time an AI coding agent gave you code that looked right but was wrong. How did you find out?
2. You must estimate the real-world size of an object from a single photo. What steps and checks would you ask an AI agent to build?
3. Paste one real prompt you recently gave an AI coding agent, and tell us what happened next.

Include a link to one piece of your work: a repository, pull request, write-up or demo.

This is a remote position.

About Leegality:

Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.

We have multiple products across 2 categories:

Document Infrastructure:

Products that help businesses build paperless processes at scale:

1. Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
2. Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contract
3. Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner

Consent Infrastructure:

1. Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
2. Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.

If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.

Curious about our impact? Explore our customer success stories: leegality.com/case-studies

Our Culture

At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.

We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:

• Flexible working hours
• Hybrid work setup
• Bi-annual performance appraisals
• A culture that rewards initiative, curiosity, and impact

If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.

Location: Hybrid

Job Brief:

• As a Machine Learning Engineer specializing in Computer Vision (CV) and Natural Language Processing (NLP), you will develop solutions to interesting technical problems, exploring exciting growth opportunities and having a real impact on our product, particularly focusing on document and content intelligence.
• To ensure success, you should demonstrate solid data science knowledge and experience in a related ML, CV, or NLP role. A first-class engineer will be someone whose expertise enhances our systems for document intelligence and content processing

Responsibilities:

• Designing machine learning systems, self-running artificial intelligence (AI) software, and specialized models for Computer Vision and Natural Language Processing applications.
• Transforming data science prototypes and applying appropriate deep learning algorithms and tools to text and image/document data.
• Solving complex CV and NLP problems with multi-layered data types, such as image/document classification, information extraction, semantic search, and object detection.
• Optimizing existing machine learning models, with a focus on high-performance model deployment for CV and NLP tasks.
• Developing ML algorithms (including large language models/LLMs and computer vision models) to analyze huge volumes of historical text, image, and document data to make predictions and automate workflows.
• Running tests, performing statistical analysis, and interpreting test results for CV/NLP model performance.
• Documenting machine learning processes, model architectures, and data pipelines.
• Keeping abreast of developments in machine learning, Computer Vision, and Natural Language Processing.

Requirements:

• 3+ years of relevant experience in Machine Learning Engineering, with a strong focus on Computer Vision and/or Natural Language Processing.
• Advanced proficiency with Python.
• Extensive knowledge of ML frameworks, libraries (e.g., PyTorch, Transformers), data structures, data modeling, and software architecture.
• Experience with building and maintaining scalable RESTful APIs (e.g., FastAPI).
• In-depth knowledge of mathematics, statistics, deep learning (CNNs, RNNs, Transformers), and algorithms.
• Superb analytical and problem-solving abilities, especially for unstructured data challenges.
• Great communication and collaboration skills.
• Excellent time management and organizational abilities.
• Experience with cloud platforms (e.g., AWS) for model deployment and MLOps.

Recruitment Process:

• Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
• You will be contacted via email with the next steps upon being shortlisted.
• The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
• Final selection and CTC will be based on your overall performance and experience.

Apply directly through our career page: https://careers.leegality.com/jobs/Careers

For more information about us please visit our:

Our Company and Culture: https://bit.ly/3Iqm5SB

Our Website: www.leegality.com/

Our LinkedIn Page: www.linkedin.com/company/leegality/

Leegality's Privacy Notice: https://www.leegality.com/employee-privacy-notice

GEMBA CONCEPTS

Experience: ~3–5 years Type: Full-time

AI/ML Engineer

Location: Bengaluru, India (Hybrid)

About Gemba Concepts

Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics

modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing

traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a

tight engineering team that ships real systems for demanding, often regulated, environments.

The Role

We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the

problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy

industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.

What You’ll Do

Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under

real factory lighting, throughput, and edge-case conditions.

Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure

prediction.

Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.

Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.

Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they

add leverage.

Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to

know when ML is not the right answer.

Communicate results and limitations clearly to non-ML stakeholders, including clients.

What We’re Looking For

3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).

Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.

Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /

anomaly detection.

Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /

Kubernetes (AKS) is a strong plus.

Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production

reality.

Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.

Nice to Have

Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).

Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).

Edge deployment experience (running CV models on-device / near the line).

Exposure to data pipeline tooling and orchestration.

What You’ll Get

Real ownership of ML systems that go into production for serious clients.

A lean, senior-heavy team where you ship fast and learn across the stack.

Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

Position Title: Real-Time Computer Vision & Edge AI Engineer (Founding Engineering Team / Core LLD) 

Reporting Structure: High-Level AI Architect (Principal ML Scientist, Google) 

Domain: Sub-16ms Edge AI, 3D Pose & Shape Estimation (SMPL-X), TensorRT C++ Inference, Zero-Copy Systems 

Performance Benchmark: Hard locked 60 FPS (<16.6 ms total frame budget) on dedicated RTX hardware

1. Position Overview & Architecture 

We are building a proprietary, ultra-low-latency spatial computing platform centered on high-fidelity 100% 3D Digital Twin architecture and real-time human digitization. 

In this role, you will serve as the Low-Level Design (LLD) Core AI Engineer, working directly alongside a Lead AI Scientist from Google. Your primary mandate is to solve complex surface occlusion and volumetric estimation challenges by building an ultra-fast C++ inference pipeline. This system must accurately regress a subject's true underlying 3D body shape and skeletal pose directly from a live camera feed. You will deploy models that extract parametric data (SMPL-X shape/pose parameters) and bridge these joint rotations seamlessly into our Vulkan graphics engine via shared GPU memory.

System Architecture: 

● Hardware Camera Ingestion: (V4L2 / GStreamer / CUDA) 

↓ Raw RGB Frames (Zero CPU Copy) 

● Edge AI Inference: (TensorRT / ONNX C++ API for 3D Pose Tracking, Kinematic Anchoring, SMPL-X Shape) 

↓ 3D Skeletal Transforms & Shape Parameters 

● Zero-Copy Shared Memory: (CUDA-Vulkan Bridge feeding directly into OpenRigLogic / MetaHuman Engine) 

2. Key Responsibilities & Deliverables 

A. Real-Time 3D Pose & Shape Estimation 

● Deploy and optimize state-of-the-art 3D human body reconstruction models (e.g., Shapy, SMPLify-X, CLIFF) to accurately regress the user's underlying skeletal structure and body volume, effectively bypassing unpredictable surface topologies and complex environmental occlusions. 

● Extract mathematically stable shape parameters (β) and pose parameters (θ) to drive the skeletal hierarchy of a high-fidelity digital avatar. 

B. Edge Inference Pipeline (TensorRT) 

● Translate Python-based research models into production-grade C++ inference engines using NVIDIA TensorRT and ONNX Runtime. 

● Implement INT8/FP16 quantization, layer fusion, and custom CUDA plugins to ensure the entire AI inference pass executes within a strict <10 ms budget per frame. 

C. Temporal Smoothing & Anti-Jitter Kinematics

● Implement highly optimized temporal filters (Kalman filters, One-Euro filters, optical flow tracking) in native C++ to eliminate all high-frequency jitter from the output joint rotations before they reach the graphics engine. 

● Ensure kinematic constraints (e.g., fixed bone lengths) are strictly maintained to prevent the digital asset from stretching or warping dynamically. 

D. Zero-Copy Ingestion & Engine Synchronization 

● Build hardware-accelerated video capture pipelines using V4L2 or GStreamer to ingest raw camera frames directly into GPU memory. 

● Bridge the output coordinate data and transformation matrices to the graphics team using POSIX shared memory and CUDA-Vulkan interop (VK_KHR_external_memory_fd), eliminating CPU staging overhead. 

3. Technical Qualifications & Tech Stack 

● Core Programming: Production-level Modern C++ (C++17/20), Python (strictly for model training/validation), and CUDA C/C++. 

● AI & Acceleration Frameworks: NVIDIA TensorRT, ONNX Runtime (C++ API), PyTorch. 

● Computer Vision Libraries: OpenCV (CUDA backend), MediaPipe C++ bindings. 

● Mathematical Foundations: 3D Kinematics, Matrix Transformations, Quaternions/Euler angles, statistical body modeling (SMPL/SMPL-X architecture). 

● Systems Architecture: Low-latency memory management, multi-threading (std::jthread, lock-free queues), SIMD vectorization. 

4. Relevant Projects & Demonstrable Experience (Preferred) 

Candidates will be preferred if they present functional codebases, GitHub repositories, or thesis work covering:

● Real-Time Body Fitting / Pose Estimation: Practical experience deploying 3D human pose or shape reconstruction models on live video feeds. 

● TensorRT / C++ Deployment: Demonstrable experience stripping a PyTorch model out of Python and running it natively in C++ using TensorRT or ONNX, ideally with custom CUDA layers or INT8 calibration. 

● High-Throughput Vision Pipelines: Built a C++ video processing pipeline that aggressively minimizes latency and avoids memory garbage collection pauses. 

● Kinematics & Smoothing: Applied mathematical filters to raw sensor or AI data to produce smooth, mechanically accurate 3D rotations. 

5. Compensation & Engagement Structure 

● Compensation: ₹1,50,000 to ₹2,00,000/month 

● Mentorship: Direct architectural guidance, algorithm review, and technical leadership from a Principal ML Scientist at Google. 

● Hardware: Dedicated high-end workstation equipped with discrete NVIDIA RTX hardware.

Hiring for AI Engineer

Exp: 5 - 8 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune

Skill Set:

Total experience ranging from 5 - 8 years in software engineering/AI roles

Min 5 years strong programming experience in Python or Typescript is a MUST

Min 2.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

Experience with cloud platforms (AWS/Azure/GCP)

About Naicos

Naicos, a fast-paced startup, builds AI-native products for algorithmic commerce: the future of how e-commerce runs. Our first products are already live with paying customers, and we are shipping new ones continuously.

Your Role

You will join the team that creates catalog imagery for sellers at scale, working closely with a Senior Engineer who will train you. You will start on well-defined tasks and grow into writing the prompts and the Python that produce the images.

Who We Are Looking For

• Total experience: 0 to 1 year, internships included

• Python: you can write and debug your own code

• No prior AI or e-commerce experience needed; we will teach you

• Final-year students and recent graduates are welcome to apply

You will be paired with a Senior Engineer and given a structured 90-day ramp. We are hiring for aptitude and attitude, not for a CV.

Skills You Bring

• Python: you can write and debug your own code. This is what we will test, and the only hard requirement.

• Curiosity about AI: you have played with ChatGPT, Claude, Gemini or image generation tools and want to build with them

• Care about detail: you notice when something looks slightly off

Good to have

• Any exposure to image editing, or to Python image libraries such as Pillow or OpenCV; college projects, hackathons or open-source work

What You Will Learn Here

• Prompt engineering for image generation models

• Image manipulation in Python: resizing and interpolation, contrast adjustment, overlaying and joining images

• How a real e-commerce catalog works, and what the marketplaces will and will not accept

Other Relevant Skills

• Communicates clearly in English, written and spoken

• Reliable and organised: you finish what you pick up, and ask for help early

• Willing to do hands-on production work while you learn; the first months mix real output with learning

Educational Qualification

• BE / B.Tech in Computer Science, IT or any engineering discipline

• BCA or MCA

• BSc / MSc in Computer Science, Maths, Statistics or Physics

• Or equivalent practical experience with a portfolio of projects

• Senior Machine Learning Engineer – Vertex AI
• Senior Generative AI Engineer – GCP
• Google Cloud AI/ML Engineer
• MLOps Engineer – Vertex AI
• LLM Engineer – RAG, Gemini, and Vertex AI