AI Engineer at 6sense
SFBA, California, USA -
Full Time


Start Date

Immediate

Expiry Date

30 Jun, 25

Salary

196075.0

Posted On

01 Apr, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Sql, R, Machine Learning, Algorithms, Automation, Computer Science, Leadership Skills

Industry

Information Technology/IT

Description

OUR MISSION:

6sense is on a mission to revolutionize how B2B organizations create revenue by predicting customers most likely to buy and recommending the best course of action to engage anonymous buying teams. 6sense Revenue AI is the only sales and marketing platform to unlock the ability to create, manage and convert high-quality pipeline to revenue.

EDUCATIONAL AND EXPERIENCE REQUIREMENTS

  • Ph.D. or Master’s in Computer Science, Data Science, or related field.
  • 5+ years in data science, machine learning, and AI, with progressive tech leadership roles.
  • Strong Python, R, SQL, and advanced statistical and ML techniques.
  • Designing tailored ML models, optimizing algorithms, and AI solution deployment.
  • Designing efficient workflows, automation, and process improvements.
  • Exceptional communication and leadership skills, managing data science teams.
  • Driving innovation, staying updated with emerging tech, and ensuring ethical compliance.
  • Effective collaboration, adaptability to changing requirements and circumstances.
Responsibilities

PURPOSE OF THE JOB

AI Engineer leads and drives advanced AI initiatives within the organization. By leveraging advanced statistical methods, machine learning, and programming, the AI Engineer is responsible for designing and implementing complex AI solutions. This role involves innovatively solving business problems, optimizing algorithms, and deploying AI models to provide data-driven insights that align with the organization’s strategic goals. Additionally, the AI Engineer ensures efficient workflows, automates processes, and effectively communicates insights to stakeholders, aiming to enhance productivity, strategic decision-making, and overall business success.

RESPONSIBILITIES & ACCOUNTABILITIES

  • Lead the design and development of complex AI solutions, employing advanced techniques to optimize algorithms and data sets for superior performance.
  • Design and implement experiments to rigorously evaluate AI solution performance and provide valuable insights for refinement.
  • Develop detailed AI solution requirements and effectively manage the development process, adapting to changing circumstances and requirements.
  • Collaborate effectively with cross-functional teams and stakeholders, ensuring successful delivery while adapting to evolving needs and circumstances.
  • Stay updated with the latest trends and advancements in AI technology, incorporating newfound knowledge into solution design and development.
  • Apply mastery of statistical methods, machine learning algorithms, and programming languages to analyze unstructured data and derive actionable insights.
  • Develop novel modeling techniques and algorithms, utilizing advanced methodologies like Bayesian inference, reinforcement learning, and causal inference.
  • Create scalable models capable of handling large volumes of real -time data, ensuring transparency and explainability in the model’s functioning.
  • Develop models that inform strategic decision-making at the highest organizational levels, leveraging advanced machine learning techniques.
  • Align business objectives with innovative data science solutions, proactively identifying opportunities for data-driven insights and product innovations.
  • Develop and implement advanced AI models, utilizing techniques like transfer learning, ensemble methods, and neural networks for complex problem -solving.
  • Design and implement efficient workflows, automate data -related tasks, and lead process improvement initiatives to enhance productivity and data accuracy.
  • Lead product development efforts, demonstrating an understanding of the business model and leveraging data for product decision-making and roadmap planning. Ethical Product Development: Understand and consider the ethical and legal implications of data-driven products and solutions, ensuring responsible and compliant development practices.
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