AI/ML Engineer – Computer Vision

AI/ML Engineer – Computer Vision

Detailed job description | Recruitment and hiring reference

Experience

1–2 years preferred; candidates with ~1 year of strong hands-on work considered

Education

B.E./B.Tech in CSE, AI/ML, ECE, IT or related discipline; M.Tech/M.Sc also welcome

Reporting to

Senior AI/ML Engineer / AI/ML Technical Lead, under CTO / Technical Director

Indicative CTC

₹5–8 LPA fixed target; flexible for demonstrated skills and budget approval

Incentives

Discretionary performance / delivery bonus, subject to approved company policy

About Eigenstate AI

Eigenstate AI is building a vision-native Industrial Intelligence platform for manufacturing. We use computer vision, video analytics and edge AI to help factories understand production activity, throughput, utilization, process adherence and operational losses. The role involves practical work on real shop-floor video data and customer pilots.

Role purpose

Build, test, fine-tune and integrate computer vision capabilities under the guidance of the technical lead. This is an individual-contributor engineering role, not a people-management or independent platform-architecture role.

Key responsibilities

· Implement computer vision features for object/person detection, tracking, segmentation, activity recognition and event counting.

· Evaluate and fine-tune open-source models (for example YOLO-family architectures) for industrial video use cases.

· Develop Python/OpenCV preprocessing, inference, post-processing and temporal event logic for production cycles and operator states.

· Prepare and curate datasets; coordinate annotation guidelines, train/validation splits and model experiments.

· Test model predictions against manually verified ground truth; calculate precision, recall, counting error and event-level accuracy.

· Investigate false positives, missed events, occlusion, camera-angle limitations and lighting changes; document root causes and fixes.

· Support RTSP/video ingestion, GPU inference, Linux deployment and integration with application APIs under team guidance.

· Write maintainable, modular, version-controlled code, tests and technical documentation.

· Contribute reusable algorithms, labeled datasets, evaluation tools and domain-specific logic to Eigenstate’s proprietary IP, respecting open-source licenses.

· Collaborate with QA, annotation, application engineers and software developers to deliver pilot milestones.

Essential skills

· Hands-on working experience with C++ and a strong understanding of object-oriented programming (OOP/OOPS) concepts.

· Good Python programming, debugging, data structures and Git fundamentals.

· Practical OpenCV and PyTorch experience; ability to run, modify, train and evaluate vision models.

· Understanding of detection, classification, tracking, image preprocessing and model evaluation.

· Experience handling images/videos, annotations and train/validation/test datasets.

· Comfort with Linux, basic command line tools, NumPy and common Python libraries.

· Ability to explain completed projects, trade-offs, errors and lessons learned clearly.

Good-to-have skills

· YOLO, ByteTrack/DeepSORT, pose estimation, action recognition or temporal modeling.

· RTSP, FFmpeg/GStreamer, ONNX, TensorRT, CUDA or edge GPU deployment.

· Docker, REST APIs, SQL, basic MLOps / experiment tracking.

· Industrial automation, robotics, manufacturing or surveillance-video analytics exposure.

Education and experience

Relevant bachelor’s degree or higher preferred. Practical projects, internships, GitHub repositories, deployed demos and demonstrable engineering capability will carry significant weight. Strong candidates with approximately one year of experience are welcome; a master’s degree is not mandatory.

Performance expectations: first 90 days

· Month 1: understand current pipelines, reproduce existing results and complete one small, reviewed feature or bug fix.

· Month 2: independently implement and validate a scoped model/logic improvement with documented metrics.

· Month 3: own a defined vision component, improve robustness and contribute reusable code/tests to the shared platform.

Compensation, incentives and benefits

· Indicative fixed CTC: ₹5–8 LPA, based on technical assessment, experience and internal pay parity; final offer subject to approval.

· Potential performance or milestone-linked incentive based on measurable delivery, code quality and validation outcomes; not guaranteed unless specified in the offer letter.

· Learning and mentorship with senior engineers; exposure to customer deployments, GPU systems and production-grade computer vision.

· Leave, statutory benefits, probation and notice period as per the company’s employment policy and applicable law.

· Any ESOP participation, if introduced, would require separate written approval and plan documentation.

Selection process

Resume and project screening → technical discussion → short practical coding/video-analytics exercise → team/culture discussion → reference and offer checks. Candidate must be able to discuss their own contributions to previous projects.

Confidentiality and intellectual property

Employee must comply with confidentiality, information-security, customer-data handling, code ownership and invention-assignment terms in the employment agreement. Open-source components must be used in accordance with their licenses. No customer footage or datasets may be published without authorization.

Pay: ₹500,000.00 - ₹800,000.00 per year

Work Location: In person