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Senior Machine Learning Engineer
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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!
Senior Machine Learning Engineer
Experience Level: 3-6 years
Job Summary
As a Senior Machine Learning Engineer at Quantiphi, you will build, deploy, and maintainproduction-grade AI/ML solutions for Fortune 500 enterprise clients on Google Cloud Platform.You'll engineer intelligent systems spanning generative AI, agentic workflows, traditionalmachine learning, and computer vision. This is a hands-on role for builders who thrive onshipping production systems that solve real business problems at enterprise scale.
Responsibilities
Generative AI & Agentic Systems - - - -
Design and implement generative AI applications including RAG systems, agenticworkflows, and multi-agent orchestration for complex business problems.
Build agentic systems combining memory, planning, and dynamic reasoning formulti-step problem-solving across enterprise datasets
Develop multi-agent architectures using modern orchestration frameworks with reliablecommunication and observability
Implement prompt engineering, context optimization, and evaluation frameworks forGenAI applications
MLOps & Production Engineering - - -
Own the complete ML lifecycle: CI/CD pipelines, automated testing, model versioning,validation gates, and progressive deployment
Build production APIs and microservices with authentication, error handling, andmonitoring design data pipelines and integrations
Monitor production ML systems, track model drift, maintain system reliability andimplement A/B testing frameworksKnowledge Solutions
Architect knowledge graph and semantic search solutions enabling entity resolution,relationship discovery, and intelligent retrieval
Design hybrid retrieval combining vector embeddings with keyword search
Client Collaboration - -
Present technical solutions to clients, translating engineering decisions into businessoutcomes
Collaborate with architects, data engineers, and business analysts on integratedsolutions
Required Qualifications - - - - -
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (orequivalent demonstrated experience)
3-6 years of hands-on ML engineering with demonstrated expertise across multiple domains (GenAI)
Expert-level Python proficiency with strong software engineering fundamentals: APIdesign, testing, containerizationProven track record shipping production ML systems in cloud environments with GCP(Vertex AI, BigQuery, Cloud Run) or equivalent
Experience building GenAI, traditional ML, and computer vision applications MLOpspractices retrieval-augmented generation
Thank you for your interest in Quantiphi! We are a team that dreams together and collaborates to ensure success. We are currently looking for exceptional individuals who can join us and contribute to a fun, diverse and hybrid work culture. As a part of the Quantiphi family, you will get ample opportunities to learn, grow and interact with colleagues from varied experience and backgrounds around the globe. If this excites you, explore our current openings and apply to any job roles that suit and interest you.
Job ID: 153887023
Skills:
Statistical Modelling, Sql, Python, Cluster Analysis, Factor Analysis, Nlp, Predictive Analysis, Pyspark, Logistic Regression, LLMs, Statistical tools and techniques, Multivariate Regression
Skills:
FastAPI, Sql, Tensorflow, Pyspark, Pandas, Pytorch, Python, Flask, XGBoost, Azure ML, Azure DevOps, scikit-learn, LightGBM
Skills:
Sql, AWS, Kubernetes, Python, Gcp, Docker, Machine Learning, Kafka, Spark, Llm, RAG, Generative AI models
Skills:
Python, LangChain, FAISS, RAG, Hugging Face, Llm
Skills:
Scipy, Keras, Pytorch, Deep Learning, Tensorflow, Python, Nlp, Machine Learning, R, scikit-learn, Data Analysis Techniques and Tools
