Staff AI Engineer
Company: 6sense
Location: San Francisco
Posted on: April 3, 2025
Job Description:
Purpose of the JobStaff AI Engineer leads and drives advanced AI
initiatives within the organization. By leveraging mastery in
advanced statistical methods, machine learning, and programming,
the Staff 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 Staff AI Engineer ensures
efficient workflows, automates processes, and effectively
communicates insights to stakeholders, aiming to enhance
productivity, strategic decision-making, and overall business
success.Job DescriptionResponsibilities & 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.Performance Measurement
- AI Solution Effectiveness: Measure the effectiveness of AI
solutions developed by assessing their impact on solving complex
business problems.
- Model Performance and Optimization: Evaluate and optimize
machine learning models to ensure they meet predefined performance
metrics and business objectives.
- Innovative Solutions Impact: Assess the impact of innovative
data science solutions on driving insights, product offerings, and
business growth.
- Efficiency and Productivity: Evaluate the efficiency and
productivity improvements achieved through process automation and
optimization.
- Stakeholder Communication: Assess the effectiveness of
communication and collaboration with stakeholders in delivering
successful AI solutions.
- Adaptability and Learning: Measure adaptability to changing
requirements and the ability to quickly learn and apply new
technologies and methodologies.
- Product Alignment and User Impact: Evaluate the alignment of
data-driven products with business goals and their impact on
improving user experiences and satisfaction.
- Ethical and Legal Compliance: Monitor compliance with ethical
and legal standards in the development of data-driven products and
solutions.Educational and Experience Requirements
- Ph.D. or Master's in Computer Science, Data Science, or related
field.
- 10+ years in data science, machine learning, and AI, with
progressive tech leadership roles.
- Expertise in 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.Competencies and Behaviors
- Expertise in advanced statistical methods, machine learning,
and programming languages (Python, R, SQL).
- Innovative Problem-Solving: Proactive in identifying innovative
data-driven insights, leveraging cutting-edge technologies, and
challenging existing approaches.
- Expertise in designing and deploying complex AI solutions,
optimizing algorithms, and integrating models effectively.
- Proficient in automating workflows, improving processes, and
enhancing efficiency in data collection, cleaning, analysis, and
reporting.
- Strong communication skills to convey complex insights to
stakeholders and effective leadership in managing data science
teams.
- Willingness to stay updated with emerging trends,
methodologies, and technologies, and adapt to changing requirements
in the field.
- Understanding and adherence to ethical and legal implications
related to data-driven products and solutions.
- Effective collaboration with cross-functional teams and
stakeholders, ensuring successful project delivery through
teamwork.
- Demonstrated contributions through research publications and
thought leadership in the data science domain.
- Ability to align data science goals with broader business
objectives, leveraging insights for strategic decision-making.
- Understanding and integrating user needs and experiences into
product development, using data to drive user-centric
decisions.
- Ability to adapt to changing requirements and circumstances,
ensuring the successful delivery of AI solutions in dynamic
environments.
- Efficiently manage time and prioritize tasks to meet project
deadlines and organizational goals.
- Commitment to maintaining high-quality standards, adhering to
compliance requirements, and ensuring data accuracy and
validity.
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Keywords: 6sense, San Francisco , Staff AI Engineer, Engineering , San Francisco, California
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