Senior AI-ML Data Scientist

Job not on LinkedIn

🔥 1 hour ago

🌐 Mexico, Argentina – Remote

🇲🇽 Mexico – Remote 🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Strategic Systems International

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1991

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Strategic Systems International (SSI) is a technology services company focused on providing innovative software solutions. With three decades of experience, SSI empowers businesses through advanced data services, artificial intelligence, and cloud computing. Their expertise spans various industries, including financial services, healthcare, and industrial supply chain. SSI's services include AI/ML, digital transformation, and SaaS applications, helping clients optimize their operations and make informed decisions. SSI is dedicated to merging physical and digital worlds, enhancing efficiency and productivity for a broad range of clients from startups to Fortune 500 companies.

📋 Description

• Own model and agent behavior end to end, from problem framing and algorithm selection through fine-tuning, retrieval design, agentic orchestration, evaluation, and production serving • Design experiments, interpret model implementations, and ship production solutions within latency budgets • Determine what agent memory should retain, in what form, and how retention is grounded in a governed data warehouse rather than an undifferentiated vector blob • Partner closely with the AI Data Engineer, who owns the warehouse, pipelines, and index infrastructure • Own the algorithm, prompt, and evaluation while collaborating on pipeline, schema, and data guarantees

🎯 Requirements

• 5–10+ years in ML/AI engineering, data science, or related technical roles • Proven experience deploying models at scale in production (LLM, CV, NLP, or multimodal) • Substantive command of machine learning algorithms and neural network theory, including optimization, regularization, attention mechanisms, tokenization, embeddings, and model internals • Rigorous grounding in inference, experimental design, and data analysis • PyTorch; TensorFlow or JAX; Hugging Face ecosystem (Transformers, Datasets, TRL) • Expert-level, production-grade Python • Strong SQL for analysis against a dimensional warehouse • Production experience with LangChain/LangGraph or equivalent and a well-considered position on agent memory architecture • Hands-on ontology design and graph-based reasoning • Expert-level deployment of AI workloads on AWS, Azure, or GCP, including GPU provisioning, cost optimization, containerization, and CI/CD • Experience with experiment tracking and model lifecycle tooling such as MLflow and Weights & Biases • Preferred: direct experience implementing CoALA or comparable cognitive architecture (SOAR, ACT-R, or documented in-house framework) in a shipped agent system • Preferred: 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: track record contributing to open-source AI frameworks or published research • Preferred: ability to lead technical discovery phases and client-facing AI workshops • Preferred: familiarity with lakehouse table formats such as Iceberg and Delta Lake