Our Mission:
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 are looking for a ML Engineer III to join the Data Science team at 6sense. This role is ideal for someone with a strong foundation in machine learning, NLP, and applied AI who can independently solve business problems and deliver production-ready solutions.
As a ML Engineer III, you will work closely with senior ML engineers, product managers, engineers, and business stakeholders to build intelligent systems that improve customer outcomes and drive business impact. You will contribute across the full machine learning lifecycle, from problem formulation and experimentation to deployment and monitoring.
The ideal candidate is technically strong, curious, execution-focused, and eager to work on modern AI systems including LLM-powered applications, retrieval systems, and intelligent automation workflows.
What You’ll Do :
- Design, develop, and deploy machine learning models and AI solutions for business and customer-facing applications.
- Build and optimize NLP and transformer-based models for classification, ranking, recommendation, prediction, and retrieval use cases.
- Contribute to GenAI and Agentic AI initiatives, including RAG pipelines, prompt engineering, tool usage, and workflow orchestration.
- Perform data exploration, feature engineering, model training, evaluation, and performance analysis.
- Develop scalable data pipelines and production workflows for model training and inference.
- Work with structured and unstructured data sources to generate actionable insights and build predictive systems.
- Partner with Product, Engineering, and Analytics teams to translate business requirements into technical solutions.
- Monitor model performance in production and contribute to model retraining, evaluation, and continuous improvement processes.
- Participate in design reviews, experimentation, and technical discussions to improve system quality and reliability.
- Document solutions, communicate findings, and present recommendations to both technical and non-technical stakeholders.
- Contribute to best practices in machine learning development, testing, deployment, and observability.
What We’re Looking For :
Required Qualifications :
- 4–6 years of experience building and deploying machine learning systems in production environments.
- Strong foundation in machine learning, statistics, experimentation, and applied data science.
- Experience developing predictive models, recommendation systems, classification models, ranking models, or related ML applications.
- Hands-on experience with NLP techniques, embeddings, transformer models, and retrieval systems.
- Experience working with Python and common machine learning libraries such as Scikit-learn, PyTorch, TensorFlow, XGBoost, or similar.
- Experience working with distributed data processing frameworks such as Spark or Databricks.
- Familiarity with model deployment, monitoring, and ML lifecycle management.
- Ability to independently execute projects with moderate ambiguity and deliver high-quality solutions.
- Strong problem-solving, analytical thinking, and communication skills.
- Ability to collaborate effectively across Data Science, Product, and Engineering teams.
Preferred Qualifications :
- Experience working with LLMs, prompt engineering, RAG systems, or agentic AI workflows.
- Familiarity with LangGraph, LangChain, Amazon Bedrock, OpenAI, Anthropic, or similar AI platforms.
- Experience with vector databases, embeddings, and semantic search systems.
- Experience with cloud platforms such as AWS.
- Experience in B2B SaaS, MarTech, AdTech, or customer-facing AI products.
- Contributions to technical blogs, open-source projects, research publications, or internal technical communities.
Our Benefits:
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 [email protected].
We are aware of recruiting impersonation attempts that are not affiliated with 6sense in any way. All email communications from 6sense will originate from the @6sense.com domain. We will not initially contact you via text message and will never request payments. If you are uncertain whether you have been contacted by an official 6sense employee, reach out to jobs@6sense.com
Skills Required
- 4-6 years of experience building and deploying machine learning systems in production environments.
- Strong foundation in machine learning, statistics, experimentation, and applied data science.
- Experience developing predictive models, recommendation systems, classification models, ranking models, or related ML applications.
- Hands-on experience with NLP techniques, embeddings, transformer models, and retrieval systems.
- Experience working with Python and common machine learning libraries such as Scikit-learn, PyTorch, TensorFlow, XGBoost, or similar.
- Experience working with distributed data processing frameworks such as Spark or Databricks.
- Familiarity with model deployment, monitoring, and ML lifecycle management.
- Ability to independently execute projects with moderate ambiguity and deliver high-quality solutions.
- Strong problem-solving, analytical thinking, and communication skills.
- Ability to collaborate effectively across Data Science, Product, and Engineering teams.
- Experience working with LLMs, prompt engineering, RAG systems, or agentic AI workflows.
- Familiarity with LangGraph, LangChain, Amazon Bedrock, OpenAI, Anthropic, or similar AI platforms.
- Experience with vector databases, embeddings, and semantic search systems.
- Experience with cloud platforms such as AWS.
- Experience in B2B SaaS, MarTech, AdTech, or customer-facing AI products.
- Contributions to technical blogs, open-source projects, research publications, or internal technical communities.
6sense Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about 6sense and has not been reviewed or approved by 6sense.
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Fair & Transparent Compensation — Pay is considered strong overall, with widespread satisfaction in salary, benefits, and equity. Compensation is also positioned as comparatively competitive for multiple roles, including sales and engineering.
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Leave & Time Off Breadth — Time-off policies are described as flexible, including an unlimited-style vacation approach and expectations of being work-free while out. This breadth in paid time off is repeatedly positioned as a standout part of the overall package.
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Healthcare Strength — Health coverage is characterized as comprehensive, with dental and vision coverage called out as employer-paid in some descriptions. Wellness-related supports such as wellness days and stipends add to the perceived strength of the health-and-wellbeing offering.
6sense Insights
What We Do
The 6sense Account Engagement Platform helps revenue teams identify and close more opportunities by putting the power of AI, big data and machine learning behind every member of the B2B revenue team.
