Responsibilities
- Lead end-to-end ML assessments across infrastructure, data pipelines, model lifecycle, and organizational readiness — producing recommendations that drive executive decision-making and earn Caylent the next engagement.
- Partner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of work.
- Serve as the senior technical authority on client engagements — possibly across multiple projects simultaneously — providing architectural guidance, ensuring technical quality from your project team members, and getting hands-on when the engagement demands it, without owning day-to-day implementation responsibilities.
- Own or orchestrate high-quality POCs that give customers confidence before committing to a larger initiative.
- Advise customers on ML operations standards and architecture — covering MLOps pipeline design, model lifecycle management, LLMOps patterns, and production monitoring frameworks — translating operational complexity into decisions and guardrails their teams can own and sustain.
- Shape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customers.
- Strengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to acceler游戏副本, reference architectures, and thought leadership content.
Tech Stack
Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI, SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation), Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI, Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly, Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue, Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate, PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama, MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness, RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation, Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo
Work Arrangement
Remote (Worldwide) — Canada, United States, Latin America
Additional Information
- Fully remote global company
- Celebrates diverse cultures of team members
- Fosters a community of technological curiosity
