Machine Learning Engineering

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 : 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**!*