Senior Machine Learning Engineer – MLOps

Job not on LinkedIn

🕒 July 30

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 43%

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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Stone & Company

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

🤝 B2B

Consulting • B2B

Stone + Company is a management and strategy consulting firm that empowers corporate clients to achieve exceptional results by transforming disjointed strategies or crafting new ones into a unified plan designed for optimal performance and team synchronization. The firm focuses on delivering fast and effective outcomes for its clients.

📋 Description

• Act as the bridge between the Data Science team and the production environment. The professional will be responsible for creating, architecting, and maintaining large-scale Machine Learning systems and pipelines, ensuring they are efficient, scalable, and have low latency.

🎯 Requirements

• Software Engineering and System Design: Strong command of coding best practices (clean code, testing, design patterns), system architecture design and documentation (C4 Model), and creating CI/CD pipelines for ML (e.g., GitHub Actions). • MLOps (Databricks-focused): Mastery of the ML lifecycle, including experiment tracking (MLflow), Feature Store management (preventing data leakage), Infrastructure as Code (Databricks Asset Bundles), cost/computation optimization, and monitoring model quality and drift. • Serving and Orchestration: Defining serving strategies (batch vs. online), building inference APIs (FastAPI, Databricks), advanced containerization (Docker), and monitoring with alerts. • Data Processing: Building scalable pipelines and distributed processing using PySpark, Spark SQL, and real-time streaming with Apache Kafka. • Engineering Background: Strong prior experience as Backend, DevOps, or SRE (working with microservices in production). • Generative AI: Experience integrating and productizing LLMs and GenAI (OpenAI, open-source models, etc.). • Analytics Engineering: Experience with dbt, Delta Lake, and data modeling. • Multi-cloud: Experience integrating and working across multiple clouds (AWS, GCP, Azure).

🏖️ Benefits

• 💸 Fixed Salary • 💰 Variable Compensation Package* (PLR, ILP, or Commission - provided according to role eligibility, not an open-choice model) • 🏥 Health and Dental Plan with copayment (except for professionals with disabilities who are exempt from copayment) • 🩺 Hospital Virtual Verde: 24/7 telemedicine team • 💊 Medication subsidy • 🍽️ Meal Allowance and/or Food Allowance - Pluxee* (except for Commercial Executive roles - 6hrs) • 👶 Childcare Assistance (for children up to 5 years and 11 months) • 💙 Financial assistance for children with disabilities • 🛡️ Life Insurance • ⛽ Fuel allowance or commuting allowance* • 🏠 Home office allowance* (only for Hybrid or Remote contracts) • 🎁 Welcome kit for new parents • 🏢 SESC partnership* • 📚 Education Benefit - Internal self-development platform (Studa and Stone Library) • 🧠 Acolhe360º - Emotional support (free) • 💆 Quick Massage and Clinic* • Wellhub - TotalPass - Pet Club - Flash - Férias&Co - VT - Allya - Educational partnerships