Machine Learning Engineering Professional

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role : Machine Learning Engineer

Experience Level : 3 to 12 years

Roles Responsibilities

Agentic AI Development: Design, develop, and optimize domain adaptive agentic AI systems that helps in automating business processes

LLM Fine-Tuning: Work with large-scale pre-trained models (like Llama, Mistral etc.) to fine-tune with techniques like PEFT, SFT and adapt them for specific applications and domains. Evaluate and Optimize for performance, accuracy, and efficiency.

Prompt Engineering: Design prompts with techniques like Chain of Thought, Few Shot to enhance model responses, ensuring that model outputs are aligned with use case requirements.

AI Workflow Automation: Build end-to-end workflows for AI solutions, from data collection and preprocessing to training, deployment, and continuous improvement in production environments.

Collaboration with Cross-functional Teams: Work closely with data scientists,

software engineers, and product managers to define AI product requirements and deliver innovative solutions.

Research Development: Stay current with the latest research and developments in generative AI, deep learning, NLP, reinforcement learning, and related fields to ensure that the organization stays at the forefront of technology.

Scaling and Deployment: Deploy machine learning models at scale, optimizing for latency, throughput, and robustness in production environments.

Documentation Reporting: Maintain clear documentation of models, workflows, and experiments, and communicate results effectively to stakeholders.

Required Skills Qualifications

Experience

3 to 5 years of hands-on experience in machine learning and AI engineering.

Proven track record in working with LLMs such as Llama, Mistral and models like

GPT, BERT, T5, or similar.

Expertise in designing, fine-tuning, and deploying generative AI models and building agentic workflows.

Strong experience in prompt engineering to optimize AI models performance.

Technical Skills

Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.

Proficiency in building agentic workflows with tools like Langgraph, CrewAI,

Autogen, PhiData or similar.

Familiarity with cloud platforms (AWS, GCP, Azure) for deployment and scaling of models.

Experience with NLP tasks, such as text classification, text generation,

summarization, and question answering.

Knowledge of reinforcement learning, multi-agent systems, or other autonomous decision-making frameworks.

Familiarity with SDLC life cycle , data processing tools (e.g., Pandas, NumPy,

etc.) and version control (e.g., Git).

Soft Skills

Strong problem-solving and analytical skills.

Excellent communication and teamwork abilities to collaborate with stakeholders.

Ability to work independently and drive projects to completion with minimal supervision.

Preferred Qualifications

Experience in deploying AI models at scale in production environments.

Expertise in large-scale data processing, optimization techniques, and model deployment.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.