AI Senior Research Engineer

Company Description

Compleren AI Labs is an innovative new startup (start date Aug 2025) in Artificial Intelligence Governance & Data Governance world. The company strives to offer state-of-the-art technical AI Compliance solutions to enterprises in EU, USA & China markets and their GCCs with presence in Indian eco-system. The focus of the company is to develop

algorithmic insights into AI Models

developed in Automotive, Medical / Health, Pharma and Finance OEMs to achieve compliance to AI Act & Data Act in EU and Colarado AI Act, CCPA Act in USA markets, especially with respect to Ethics, Privacy, Explainability and Security. The company is led by its Chief Researcher-AI Governance who has previously worked as AI & Data Governance Team Member of Mercedes-Benz AG and long experience in SW development & product compliance for Mercedes-Benz R & D India. The company will be recruiting curious and passionate young AI researchers for its Proof-of-Concept Projects for Multiple Industries. Creative and committed young engineers will be offered to choose the flexibility to choose ESOPs. The business will also be expanded to AI Model development in the near future.

Role Description

This is an on-site full-time role for an AI Senior Research Engineer based in Bengaluru. The engineer will be responsible for researching methods and tools for generating KPIs that best describe the risks of using AI models in particular use-cases in automotive industry

Description of AI Compliance requirements for EU markets

Implementation of above methods in Python

Techno-legal documentation from scanning the AI Models using above implementation for compliance

Required skills and qualifications

Candidates for an AI researcher position should have a mix of strong technical and soft skills.

Technical skills

Advanced education : A Master's degree in Computer Science, AI, Machine Learning, or a related field is

Deep learning frameworks : Proficiency in platforms like PyTorch or TensorFlow.

Programming languages : Expertise in Python is a must, with knowledge of other languages like C++ or R often preferred.

Mathematical background : Strong understanding of statistics, linear algebra, and calculus.

Algorithm development : Experience designing, testing, and optimizing machine learning algorithms.

AI architectures : Familiarity with deep learning architectures, including transformers, generative adversarial networks (GANs), and reinforcement learning.

Soft skills

Problem-solving : Ability to approach complex challenges creatively and analytically.

Communication : Excellent written and verbal communication to present complex ideas to both technical and non-technical audiences.

Collaboration : A team-oriented mindset for working with other researchers and engineering teams.

Intellectual curiosity : A passion for continuous learning and staying current with rapid advancements in the field.

Adaptability : Ability to work in a fast-paced, dynamic environment and manage shifting project priorities.