Machine Learning Engineer
2 days ago
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
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
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 & IPs
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