Quantiphi
Machine Learning Engineer
Job Description
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 : 1 to 3 years
Location : Mumbai / Bangalore / Trivandrum (Hybrid)
Notice Period : 0-30 days
Roles & Responsibilities:
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Agentic AI Development: Design, develop, and optimize domain adaptive agentic AI systems that helps in automating business processes.
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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.
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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.
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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.
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Collaboration with Cross-functional Teams: Work closely with data scientists, software engineers, and product managers to define AI product requirements and deliver innovative solutions.
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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.
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Scaling and Deployment: Deploy machine learning models at scale, optimizing for latency, throughput, and robustness in production environments.
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Documentation & Reporting: Maintain clear documentation of models, workflows, and experiments, and communicate results effectively to stakeholders.
Required Skills & Qualifications:
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Experience:
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1 to 3 years of hands-on experience in machine learning and AI engineering.
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Proven track record in working with LLMs such as Llama, Mistral and models like GPT, BERT, T5, or similar.
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Expertise in designing, fine-tuning, and deploying generative AI models and building agentic workflows.
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Strong experience in prompt engineering to optimize AI models performance.
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Technical Skills:
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Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
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Proficiency in building agentic workflows with tools like Langgraph, CrewAI, Autogen, PhiData or similar.
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Familiarity with cloud platforms (AWS, GCP, Azure) for deployment and scaling of models.
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Experience with NLP tasks, such as text classification, text generation, summarization, and question answering.
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Knowledge of reinforcement learning, multi-agent systems, or other autonomous decision-making frameworks.
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Familiarity with SDLC life cycle , data processing tools (e.g., Pandas, NumPy, etc.) and version control (e.g., Git).
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Soft Skills:
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Strong problem-solving and analytical skills.
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Excellent communication and teamwork abilities to collaborate with stakeholders.
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Ability to work independently and drive projects to completion with minimal supervision.
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Preferred Qualifications:
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Experience in deploying AI models at scale in production environments.
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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!