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.