66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential.
At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.
A 66degrees AI/ML Architect is a multifaceted professional responsible for leading the technical development and implementation of AI/ML solutions, managing client relationships, and ensuring the delivery of business value. They serve as the primary technical point of contact for clients and act as the bridge between them and our delivery team.
Beyond their role as technical leaders, AI/ML Architects are strategic partners to clients, ensuring that AI/ML projects are successfully executed and deliver significant business value. They balance technical expertise with strong client management and project oversight skills. Additionally, they identify and inform about upselling opportunities within their client engagements to continue growing our relationship with the client.
AI/ML Architects are the frontline representatives of this team to the broader organization, Google, and clients. The strength of our brand is reflected in the capabilities and leadership of the architects who lead this team.
Duration: 4+ Months
Targeted start date: Mid June
ResponsibilitiesAn AI/ML architect in the AI/ML domain has four main roles: Project Leader, Trusted Advisor, Thought Leader and Mentor.
Project Leader
An AI/ML architect is responsible for serving as the primary technical point of contact for the client. Their key responsibilities of this role include:
- Gathering Requirements: Engaging with clients to understand their needs and requirements for the solution.
- Designing Solutions: Creating tailored solutions that meet client specifications and business goals.
- Client Communication: Maintaining clear and effective communication with the client throughout the project lifecycle.
- Identifying and Mitigating Risk:
- Scope Creep: Monitoring the project to ensure it stays within the defined scope and managing any changes or expansions.
- Identifying Resource Issues: Recognizing and escalating any resource constraints or issues that could impact project delivery.
- Building Sprints: Planning and organizing work into sprints alongside the DM to ensure timely and efficient delivery of the project.
- Bridging Gaps: Facilitating collaboration between different teams to ensure seamless integration and delivery of the AI/ML solution.
- Ensuring Ethical AI: Implementing ethical AI practices, including:
- Fairness: Ensuring that AI models are free from biases and provide fair and unbiased results.
- Interpretability: Maintaining transparency in AI/ML processes and decisions, making it easy for clients and end-users to understand how decisions are made.
- Privacy: Adhering to regulatory requirements and industry standards related to AI and data privacy, ensuring that personal data is protected.
- Safety and Security: Ensuring that AI systems are secure from malicious attacks and operate safely to prevent harm to users or the public.
- In addition to these technical responsibilities, the architect is tasked with managing client relationships, ensuring client satisfaction, and delivering tangible value. They are not just technical leaders but also project managers and client advocates, ensuring the successful implementation of AI/ML projects.
Trusted Advisor
AI/ML architects strive to become trusted advisors to their clients. This involves:
- Building Trust: Establishing strong, trust-based relationships with clients.
- Ensuring Value: Ensuring that AI/ML projects deliver significant business value and meet client objectives.
- Providing Expertise: Offering expert advice and insights on AI/ML strategies and solutions.
- Identifying Opportunities: Recognizing and communicating to sales upselling opportunities to deliver additional value to clients.
- Thought Leader
- As a Thought Leader, AI/ML architects lead the technical competencies of this team:
- Staying Informed: Keeping abreast of the latest research, trends, and innovations in AI/ML.
- Professional Development: Continuously improving their own skills through courses, certifications, and industry conferences.
- Fostering Innovation: Promoting a culture of innovation within their team by encouraging new ideas and experimenting with cutting-edge technologies.
- Tool and Technology Evaluation: Assessing and integrating the latest tools and technologies to enhance AI/ML solutions and improve project outcomes.
- Knowledge Sharing: Sharing expertise and insights with their team and the broader organization to foster a learning environment and keep everyone updated on industry trends.
- By emphasizing continuous learning, innovation, and leadership in AI/ML, architects ensure their solutions remain at the forefront of technology, delivering maximum value to clients and maintaining a competitive edge in the industry.
Mentor
An architect's role extends beyond technical expertise; it includes mentoring engineers and facilitating knowledge sharing across the team and organization. By nurturing team members and fostering collaboration, architects ensure continuous growth and success in AI/ML initiatives.
Architects also significantly contribute to the feedback loop with managers. Leveraging their deep understanding of team dynamics and individual capabilities, they provide valuable insights that help managers refine their coaching strategies and tailor development plans to ensure each team member receives the necessary support for growth and success.
Qualifications
- 6+ years of experience with data science.
- Deep practical execution across complex multi-variable linear/logistic regression, time-series forecasting, and structural classification models (e.g., gradient boosting, random forests).
- Experience with large-scale multi-dimensional clustering, propensity segmenting, and custom anomaly detection (e.g., Isolation Forests).
- Hands-on model customization utilizing frameworks like PyTorch, TensorFlow, Keras, or specialized toolsets (e.g., MONAI for computer vision, spaCy/Hugging Face for NLP).
- Proven experience designing autonomous, state-managed agentic workflows that extend past simple vector database retrieval.
- Practical, production-level code deployment utilizing advanced multi-agent frameworks, specifically LangGraph, LangChain, or AutoGen.
- Hands-on competency implementation with Model Context Protocol (MCP) patterns, programmatic tool calling, multi-step execution planning, and policy-guarded autonomous reasoning loops.
- Proven experience taking models completely from POC to enterprise deployment, configuring automated model validation, endpoint serving, and data/model drift monitoring metrics (e.g., Vertex Pipelines, Kubeflow, Airflow, or MLflow).
- trong software engineering fundamentals with expert-level Python and SQL. Deep immersion with Docker, Kubernetes, and setting up Git-backed testing frameworks (CI/CD/CT).
- Deep experience extracting, cleansing, and transforming fragmented, massive data streams into scalable, unified data estates across Snowflake, BigQuery, or related data lakes.
- Ability to track changing business requirements and deliver quality solutions both independently and with teams of varying skill sets.
- Bachelor’s degree in Data Science, Computer Science or similar.
- Experience with Google Cloud Platform
66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class.
AI Transparency & DisclosureAs an AI transformation partner, 66degrees leverages intelligent solutions to enhance our recruitment experience. We utilize AI tools—including LinkedIn Recruiter’s Hiring Assistant and interview transcription technologies—to assist with sourcing, role analysis, and capturing interview highlights.
These tools augment our process, but we "Commit to Our Craft" by ensuring all final hiring decisions are made by our human Talent Team. By applying, you acknowledge the use of these technologies to help us "Win Together" in finding the best fit for our team.
