Machine Learning Engineer

Overview

About Artikate Studio

Artikate Studio is a fast-growing product engineering and AI innovation company working with global startups, government bodies and enterprises across the US, Europe, Middle East, and India. We build intelligent digital products—end-to-end—from idea to launch: full-stack apps, AI/ML systems, cloud infrastructure, data platforms and advanced automation.

We’ve built IPs like Artikate [iQ], PsyOps Stack, and Drone Intelligence Systems, and we’re expanding our machine learning team to power the next generation of AI-enabled products.

If you love solving real-world problems with AI, experimenting with cutting-edge models, and building production systems that scale—let’s talk.

Role Overview

We’re looking for a Machine Learning Engineer who can own the full lifecycle of ML development—from research and prototyping to deployment and monitoring. You’ll work closely with our product engineering teams, founders, and clients to build AI systems across domains such as:

• NLP, LLMs & GenAI
• Computer Vision
• Predictive Analytics
• Recommendation Systems
• Autonomous Systems / Robotics
• Custom AI for enterprise workflows

This role is ideal for someone who thrives in a fast-paced, product-driven, engineering-first environment.

Responsibilities

Machine Learning Development

• Design, develop, and deploy ML models for production-grade applications
• Experiment with LLMs, embeddings, RAG pipelines, agentic workflows, and model fine-tuning
• Build robust computer vision and NLP models tailored to real-world use cases
• Implement data pipelines, feature stores, and model versioning (MLOps best practices)

Architecture & Engineering

• Architect scalable ML systems on AWS, GCP, or Azure
• Deploy microservices, APIs, and containerized workloads
• Own the ML development lifecycle: data → model → evaluation → deployment → monitoring

Research & Innovation

• Explore state-of-the-art advancements (transformers, diffusion, multimodal, reinforcement learning)
• Prototype POCs rapidly and iterate with engineering teams
• Drive internal ML frameworks and reusable components

Collaboration

• Work directly with founders, product managers, and cross-functional engineering pods
• Lead technical discussions with clients and guide them on AI strategy
• Mentor junior ML engineers and contribute to a strong ML culture

Requirements

Technical Must-Haves

• 2–4 years of hands-on experience in machine learning or deep learning
• Strong programming skills in Python, along with ML frameworks like TensorFlow, PyTorch, scikit-learn
• Experience with LLMs, vector databases, embeddings, RAG systems, or model fine-tuning
• Strong understanding of data structures, algorithms, and applied mathematics
• Hands-on experience deploying models in production (Docker, REST API, microservices)
• Solid cloud experience with AWS/GCP/Azure
• Familiarity with MLOps tools like MLflow, Kubeflow, Airflow, or Vertex AI

Nice-to-Haves

• Experience with on-device ML / optimization / quantization
• Knowledge of reinforcement learning or multimodal models
• Experience working in startup/agency-style rapid execution environment
• Understanding of DevOps fundamentals (CI/CD, infra-as-code)

What We Offer

• Competitive salary + performance-based bonuses
• Flexible hybrid work options
• Work on global & govt projects with cutting-edge AI technologies
• Opportunity to lead end-to-end AI product development
• Fast growth environment with high ownership and autonomy
• A tight engineering-focused culture
• Opportunity to contribute to Artikate Studio’s in-house AI products & IP