Associate Technical Architect – ML

This is a fully remote position, open to applicants in Canada.

📋 Description

• Create and develop sophisticated machine learning models and algorithms to address intricate business challenges.

• Enhance and deploy machine learning models on AWS infrastructure.

• Guarantee model scalability and dependability.

• Design prompts and refine few-shot techniques for specific applications, such as personalized recommendations.

• Assess the zero-shot and few-shot capabilities of large language models (LLMs).

• Adjust hyperparameters and ensure generalization across tasks.

• Investigate model interpretability for effective integration into web applications.

• Work alongside machine learning and integration engineers to provide contextually relevant responses in a user-friendly web application.

• Implement and oversee MLOps principles and best practices for Generative AI models.

• Architect software solutions and end-to-end processes for model training, deployment, and retraining.

• Collaborate with developers, quality assurance, project managers, and other stakeholders to gather requirements and deliver solutions.

⛳️ Requirements

• Over 8 years of relevant hands-on technical experience in developing and implementing cloud ML solutions on AWS.

• Practical experience with AWS Machine Learning services.

• Demonstrated proficiency in utilizing AWS SageMaker with various data sources, training jobs, real-time and batch inference, as well as processing jobs.

• Experience in developing applications using large language models (LLMs) with LangChain.

• Familiarity with Generative AI frameworks such as Vertex AI, OpenAI, and AWS Bedrock.

• Direct experience in fine-tuning large language models and Generative AI, particularly Llama 2.

• Practical experience with Retrieval Augmented Generation (RAG) architecture.

• Knowledge of vector indexing tools like OpenSearch and Elasticsearch.

• Strong awareness of LLM trends and open-source platforms.

• Background in deep learning concepts, including Transformers, BERT, and attention models.

• Expertise in prompt engineering and few-shot optimization.

• Experience in LLM evaluation, hyperparameter tuning, task generalization, and model interpretability.

• Knowledge of MLOps principles and best practices specifically for Generative AI models.

• Comprehensive understanding of NLP techniques for text representation and modeling.

• Capability to design software architecture.

• Experience with at least one workflow orchestration tool: Airflow, Step Functions, SageMaker Pipelines, or Kubeflow.

• Understanding of supervised and unsupervised machine learning techniques, including clustering, decision trees, and artificial neural networks.

• Ability to create end-to-end solution architecture for model training, deployment, and retraining using native AWS services like SageMaker and Lambda.

• Skill in collaborating with developers, quality assurance, project managers, and other stakeholders.

• A Bachelor's degree or equivalent work experience is not specified.

🏝️ Benefits

• Become a part of one of the world's fastest-growing AI-first digital engineering firms and make a significant impact at scale.

• Lead and collaborate with a dynamic team of talented, motivated individuals tackling complex and meaningful challenges.

• Engage with Fortune 500 companies and innovative disruptors in a research-focused environment with over 60 patents.

• Gain hands-on experience with state-of-the-art AI, ML, data, and cloud technologies.

• Enjoy continuous upskilling opportunities.

• Thrive in a global, diverse culture founded on transparency, diversity, integrity, learning, and growth.