Senior AI-ML Data Scientist

This is a fully remote position, open to applicants in Mexico, +1 more country.

📋 Description

• Take ownership of model and agent behavior throughout the entire process, from defining the problem and selecting algorithms to fine-tuning, retrieval design, agent orchestration, evaluation, and deployment in production.

• Design experiments, analyze model implementations, and deliver production solutions that adhere to latency requirements.

• Establish what information agent memory should retain, the format it should take, and ensure that retention is based on a governed data warehouse rather than an indistinguishable vector blob.

• Collaborate closely with the AI Data Engineer, who is responsible for the warehouse, data pipelines, and indexing infrastructure.

• Manage the algorithm, prompts, and evaluation processes while working in partnership on pipelines, schemas, and data assurances.

⛳️ Requirements

• 5–10+ years of experience in ML/AI engineering, data science, or related technical fields.

• Demonstrated expertise in deploying models at scale in production environments (LLM, CV, NLP, or multimodal).

• Strong understanding of machine learning algorithms and neural network principles, including optimization, regularization, attention mechanisms, tokenization, embeddings, and model internals.

• Solid foundation in inference, experimental design, and data analysis.

• Proficiency in PyTorch; experience with TensorFlow or JAX; familiarity with the Hugging Face ecosystem (Transformers, Datasets, TRL).

• Expert-level proficiency in production-grade Python.

• Strong SQL skills for analysis against a dimensional data warehouse.

• Experience in production environments with LangChain/LangGraph or similar, along with a well-thought-out perspective on agent memory architecture.

• Practical knowledge in ontology design and graph-based reasoning.

• Expert-level experience deploying AI workloads on AWS, Azure, or GCP, including GPU provisioning, cost optimization, containerization, and CI/CD practices.

• Familiarity with experiment tracking and model lifecycle tools such as MLflow and Weights & Biases.

• Preferred: direct experience in implementing CoALA or a similar cognitive architecture (SOAR, ACT-R, or an equivalent in-house framework) within a delivered agent system.

• Preferred: knowledge of GPU acceleration internals, including CUDA, TensorRT, and cuBLAS.

• Preferred: production experience with vLLM, NVIDIA Triton, Ray Serve/Ray Train, DeepSpeed, or FSDP.

• Preferred: experience with AI security, governance, and compliance frameworks.

• Preferred: a history of contributions to open-source AI frameworks or published research.

• Preferred: capability to lead technical discovery phases and facilitate client-facing AI workshops.

• Preferred: familiarity with lakehouse table formats such as Iceberg and Delta Lake.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• Engaging company culture with team-building activities.