Sr. Machine Learning Engineer New Bengaluru, Karnataka, India

6sense; Northern (KY); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health coverage

Paid parental leave

Stock options

Generous PTO

Job summary

6sense is seeking a Sr. Machine Learning Engineer to join the ML Engineering team. The role focuses on production systems that ensure dependable ML at massive scale, including model-training pipelines, evaluation and release controls, and high-throughput inference.

You will work with Data Scientists, platform engineers, and product teams to turn experimentation into governed, observable, scalable production systems and help shape evaluation, promotion, monitoring, and reliability.

Qualifications

• 6+ years of industry experience building and operating production machine-learning or data-intensive distributed systems.
• Strong Python engineering skills and practical experience designing maintainable services and pipelines.
• Demonstrated MLOps depth: experiment tracking, model registry/versioning, CI/CD, reproducible training, deployment strategies, monitoring.

Responsibilities

• Own production ML capabilities end to end: turn a business need into a pipeline or service, then operate and improve it in production.
• Build and evolve training, model-refresh, feature/data-validation, and inference workflows across batch and real-time use cases.
• Design model lifecycle controls: experiment tracking, evaluation gates, rollout, rollback, lineage, reproducibility, and monitoring.
• Build platform primitives that enable data science and AI product teams to ship faster while maintaining reliability and cost.
• Improve performance and observability of distributed ML workloads and model-serving systems.
• Collaborate with Data Science on evaluation design, data quality, model-health signals, and production debugging.

Skills

Python

MLOps

Distributed systems

Data pipelines

Tools

Spark

Ray

Databricks

Kubernetes

AWS

Job description

6sense's mission is to multiply what matters: growth, retention, and efficiency. We envision a future where companies, teams and people reach their full potential.

Our People:

People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging. Every 6sensor plays a part in defining the future of our industry-leading technology. 6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers. We want 6sense to be the best chapter of your career.

About the Role :

We're hiring a Sr. Machine Learning Engineer to join the ML Engineering team. Our team builds the production systems that make 6sense's machine learning dependable at massive scale: model-training and refresh pipelines, evaluation and release controls, high-throughput batch and online inference, and the shared platforms that let Data Science and product teams ship safely.

This is a hands-on engineering role for someone who enjoys owning the hard middle between a strong model and a reliable customer capability. You will work closely with Data Scientists, platform engineers, and product teams to turn experimentation into governed, observable, scalable production systems. You will help shape how models and AI agents are evaluated, promoted, monitored, and improved—not simply deploy them once.

What You'll Do :

• Own production ML capabilities end to end: turn a business or modeling need into a well-designed pipeline or service, then operate and improve it in production.
• Build and evolve scalable training, model-refresh, feature/data-validation, and inference workflows across batch and real-time use cases.
• Design reliable model lifecycle controls: experiment tracking, evaluation gates, model/version promotion, rollback, lineage, reproducibility, and monitoring.
• Build platform primitives that enable Data Science and AI product teams to ship faster without compromising reliability, security, or cost.
• Improve the performance, resilience, and observability of distributed ML workloads and model-serving systems.
• Partner with Data Science on evaluation design, data quality, model-health signals, and production debugging.
• Contribute to LLM/agent evaluation and serving infrastructure where appropriate, including offline and online evaluation, tracing, quality gates, and regression detection.
• Lead technical design for ambiguous projects, influence architecture across teams, and mentor engineers through code reviews and hands-on guidance.
• Communicate decisions, risks, and operational status clearly to engineering, product, and leadership stakeholders.

What We’re Looking For :

Required :

• 6+ years of industry experience building and operating production machine-learning or data-intensive distributed systems, including substantial end-to-end ownership.
• Strong Python engineering skills and practical experience designing maintainable, testable services and pipelines.
• Demonstrated MLOps depth: experiment tracking, model registry/versioning, CI/CD, reproducible training, data/model validation, deployment strategies, rollback, and production monitoring.
• Experience with distributed data and ML infrastructure such as Spark, Ray, Databricks, Kubernetes, AWS, or equivalent platforms.
• Strong understanding of model-training and inference trade-offs: data quality, feature engineering, evaluation, latency/throughput, cost, reliability, and model drift.
• Experience productionizing at least one of: classical ML models, deep-learning/NLP models, embedding/retrieval systems, or LLM/agent workflows.
• Solid judgment in incident response and operational ownership; able to diagnose failures across data, model, infrastructure, and serving layers.
• Ability to translate ambiguous product and Data Science requirements into a pragmatic technical plan and drive it to completion.
• Clear written and verbal communication with both technical and non-technical partners.

Nice to Have :

• Hands-on experience with MLflow, Databricks, Ray, Kubernetes, Triton/managed model serving, or similar ML platform tooling.
• Experience operating high-volume batch scoring or low-latency online inference systems.
• Experience with LLM/agent evaluation frameworks, tracing/observability, RAG, vector search, LangGraph/LangSmith, or Amazon Bedrock.
• Experience with feature stores, data contracts, schema validation, and data-quality systems.
• Experience in B2B SaaS or a high-scale data platform where reliability and customer impact matter.

Full-time employees can take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. We'll make sure you have the equipment and support you need to work and connect with your teams, at home or in one of our offices.

We have a growth mindset culture that is represented in all that we do, from onboarding through to numerous learning and development initiatives including access to our LinkedIn Learning platform. Employee well-being is also top of mind for us. We host quarterly wellness education sessions to encourage self care and personal growth. From wellness days to ERG-hosted events, we celebrate and energize all 6sense employees and their backgrounds.

Equal Opportunity Employer:

6sense is an Equal Employment Opportunity and affirmative action employers. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to [e-mail].

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in 6sense’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A \"disabled veteran\" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A \"recently separated veteran\" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An \"active duty wartime or campaign badge veteran\" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An \"Armed forces service medal veteran\" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.