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 maintain production-grade AI/ML solutions for Fortune 500 enterprise clients on Google Cloud Platform. You'll engineer intelligent systems spanning generative AI, agentic workflows, traditional machine learning, and computer vision. This is a hands-on role for builders who thrive on shipping production systems that solve real business problems at enterprise scale.
Responsibilities
Generative AI & Agentic Systems - - - -
Design and implement generative AI applications including RAG systems, agentic workflows, and multi-agent orchestration for complex business problems.
Build agentic systems combining memory, planning, and dynamic reasoning for multi-step problem-solving across enterprise datasets
Develop multi-agent architectures using modern orchestration frameworks with reliable communication and observability
Implement prompt engineering, context optimization, and evaluation frameworks for GenAI 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, and monitoring; design data pipelines and integrations
Monitor production ML systems, track model drift, maintain system reliability and implement A/B testing frameworks Knowledge 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 business outcomes
Collaborate with architects, data engineers, and business analysts on integrated solutions
Required Qualifications - - - - -
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent 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: API design, testing, containerization Proven 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; MLOps practices; retrieval-augmented generation
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Skills Required
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent demonstrated experience
- 3-6 years of hands-on machine learning engineering experience
- Expert-level Python proficiency
- Strong software engineering fundamentals, including API design, testing, and containerization
- Experience shipping production machine learning systems in cloud environments
- Experience with Google Cloud Platform, including Vertex AI, BigQuery, and Cloud Run, or equivalent
- Experience building generative AI, traditional machine learning, and computer vision applications
- Experience with MLOps practices
- Experience with retrieval-augmented generation
Quantiphi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Quantiphi and has not been reviewed or approved by Quantiphi.
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Wellbeing & Lifestyle Benefits — Wellbeing initiatives such as monthly meeting-free AMA-Zen Days, health check-ups, and wellness counseling are designed to reduce burnout and support day-to-day balance. Broader wellness programs reinforce both physical and mental health.
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Flexible Benefits — Remote/hybrid options with flexible working hours provide meaningful autonomy over where and when work gets done. Flexible leave constructs, including sabbaticals and special day leaves, add practical adaptability to the package.
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Parental & Family Support — Paid parental leave in the U.S., alongside maternity and childcare support, signals solid backing for families. These family-oriented policies integrate with a wider health and wellness focus.
Quantiphi Insights
What We Do
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.
