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!