Principal AI/ML Architect at 3Pillar
Remote, , Costa Rica -
Full Time


Start Date

Immediate

Expiry Date

25 Jul, 25

Salary

0.0

Posted On

26 Apr, 25

Experience

12 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Communication Skills, Computer Science, Data Science, Python, Structured Data, Containerization, Journals, Docker, Machine Learning, Microservices, Data Governance, Algorithms, Mathematics, Learning Theory

Industry

Computer Software/Engineering

Description

Accomplished Tech Visionary:
Embark on an exciting journey into the realm of software development with 3Pillar! We extend an invitation for you to join our team and gear up for a thrilling adventure. As an AI/ML Architect, you will lead the design and implementation of AI and ML systems that power intelligent features across our products and platforms. You will define scalable, secure, and production-ready architectures leveraging classical ML, and deep learning and other AI technologies.
If you are passionate about discovering solutions hidden in large data sets to improve business outcomes, consider this your pass to the captivating world of Data Science and AI ML!

MINIMUM QUALIFICATIONS

  • Master’s degree in Computer Science, Engineering, Mathematics, or a related field with 12+ years of industry experience in machine learning or data science, with a track record of delivering impactful projects; a Ph.D. is highly desirable.
  • Good undertaking of Software Product Development and how to integrate AI ML components into a software product.
  • Experience working with massive amounts of non-structured data.
  • Strong grasp of AI architecture patterns.
  • Expertise in AWS Sage Maker.
  • Deep experience with Python, ML libraries (scikit-learn, XGBoost, PyTorch, TensorFlow).
  • Experience designing enterprise AI systems with MLOps (MLflow, Kubeflow, SageMaker Pipelines).
  • Experience with APIs, microservices, and containerization (Docker, Kubernetes).
  • Experience in Data Governance, Model Risk Management, and compliance.
  • Extensive knowledge of machine learning theory, algorithms, and methodologies.
  • Strong leadership and communication skills, with the ability to influence stakeholders at all levels of the organization.
  • Demonstrated ability to think strategically and drive innovation.
  • Experience in working with huge datasets in a production environment.

ADDITIONAL EXPERIENCE DESIRED

  • Published research in top-tier conferences or journals is a plus.
  • Experience working with GenAI technologies.
Responsibilities
  • Maintain current ML models working throughout different products in the cybersecurity space.
  • Define end-to-end architecture for AI/ML AI systems including data pipelines, model training/inference, and MLOps.
  • Working with Classification and other types of Models.
  • Regularly going to CCB (change control board) in products’ related meetings.
  • Implement models’ Testing strategies.
  • Serve as a strategic technical advisor to the client, leading solution design discussions, presenting AI/ML architectures, and representing 3Pillar in client-facing interactions to drive innovation and business value.
  • Architect scalable solutions using cloud-native AI tools in AWS SageMaker, AWS Lambda, S3, RDS, Glue, Kinesis firehose, SQS, SNS, API Gateway.
  • VPN management.
  • Fix/Improve Models Evolution and Life Cycle Strategy.
  • Fix/Improve Models Deployment strategy.
  • Guide teams on MLOps frameworks for CI/CD, model versioning, monitoring, and automated retraining.
  • Evaluate build-vs-buy decisions and benchmark AI models/tools/platforms.
  • Evaluate emerging technologies and trends in AI, ML, Gen AI space and recommend adoption strategies.
  • Mentor technical teams and guide solution architects, data engineers, and ML engineers.
  • Ensure ethical and responsible AI practices including bias detection, interpretability, and governance.
  • Act as a subject matter expert, providing guidance and mentorship to junior colleagues and strengthen the expertise in the organization.
  • Collaborate with leadership to align machine learning strategies with overall business objectives.
  • Participation in Software Engineering cross-products-interaction activities developing with APIs and AWS Services.
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