Job Description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Associate Principal Engineer, Machine Learning based in India.

This role is a senior AI/ML architecture position focused on designing and delivering scalable, production-grade machine learning solutions across complex enterprise environments. You will work on end-to-end AI systems spanning data pipelines, model development, deployment, and monitoring, with strong emphasis on real-world impact. The position involves building advanced solutions across NLP, computer vision, and generative AI, including LLM-based systems and agentic architectures. You will collaborate closely with business and technical stakeholders to translate requirements into robust, scalable, and secure ML solutions. The environment is highly technical, innovation-driven, and cloud-centric, with strong focus on MLOps, automation, and responsible AI practices. This is a leadership-level engineering role where you will influence architecture decisions and shape the direction of AI solutions at scale.

Accountabilities:

Design and architect end-to-end machine learning and AI solutions aligned with business and technical requirements
Translate complex business use cases into scalable, production-ready ML system designs and technical architectures
Lead design decisions across data pipelines, model training, deployment, and monitoring in cloud-based environments
Define AI/ML architecture standards, guidelines, and best practices including NFRs such as scalability, security, and performance
Develop and review architecture and design documentation, ensuring clarity for engineering implementation teams
Evaluate and select optimal ML approaches, tools, frameworks, and technologies based on client requirements
Design and guide development of AI/ML solutions across NLP, computer vision, and generative AI domains
Build and oversee implementation of MLOps pipelines using tools such as MLflow, Kubeflow, Docker, and Kubernetes
Design and deploy AI agents and multi-agent systems for autonomous or semi-autonomous decision-making
Lead proof-of-concept initiatives to validate architectures, frameworks, and emerging AI technologies
Ensure adherence to responsible AI principles, model governance, and ethical AI practices
Troubleshoot complex system issues through root-cause analysis and technical deep-dives

Requirements

9+ years of experience in machine learning, AI engineering, or data science roles with strong architectural exposure
Proven experience delivering production-grade ML solutions across NLP, computer vision, or AI-driven systems
Strong expertise in AI/ML architecture design on cloud and big data environments
Advanced programming skills in Python, with experience using libraries such as Pandas, NumPy, and Scikit-learn
Strong hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX
Solid understanding of statistical methods and their application in real-world ML problems
Experience working with SQL and large-scale data processing systems
Strong knowledge of MLOps practices and tools such as MLflow, Kubeflow, Docker, and Kubernetes
Experience designing and deploying AI agents and multi-agent systems
Strong understanding of LLMs, foundation models, prompt engineering, and RAG-based architectures
Experience with generative AI techniques including GANs and VAEs is highly desirable
Strong analytical, problem-solving, and system design skills
Excellent communication and stakeholder management abilities across technical and business teams
Experience applying responsible AI principles and ethical AI frameworks

Benefits

Competitive compensation aligned with senior AI engineering roles
Flexible and remote-friendly work environment
Opportunity to work on cutting-edge AI, LLM, and agentic systems
Exposure to large-scale enterprise AI transformation programs
Continuous learning and professional development opportunities in advanced AI domains
Collaborative, non-hierarchical engineering culture focused on innovation
Opportunity to influence AI architecture decisions across complex global projects.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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About Jobgether

Jobgether is an AI-powered career coach and matching platform fixing the broken job search. Remote professionals no longer waste hours applying blindly; instead, they receive a personalized job search strategy, stronger visibility, and curated matches aligned with their skills, flexibility preferences, and career goals.

We flip the hiring model by connecting talent only to roles that truly match, reducing noise for employers and eliminating wasted effort for candidates. Jobgether combines AI coaching, profile optimization, Match Score insights, and the world’s largest remote job database to help people land opportunities faster and with less bias.

Our purpose is to make remote job search guided and intentional.

Our mission is to become the world’s reference platform for remote talent, ensuring no professional remains invisible and every match is meaningful.

Industry

Retail & Ecommerce

Company Size

201-500 employees

Headquarters

Brussels, BE

Year Founded

2020

Website

jobgether.com

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