Machine Learning Engineering

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.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!