Senior MLOps Engineer – Real-Time ML

Job not on LinkedIn

🔥 1 minute ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 10%

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ASAAS

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2010

💼 Consulting

🏥 Healthcare

🏨 Hospitality

Consulting • Healthcare • Hospitality

ASAAS is a leading producer of 360° virtual tours in virtual reality. The company specializes in creating customized virtual tours, utilizing advanced technologies, including 360° video, drone technology, and interactive features, to enhance business visibility and engagement. With a commitment to quality and customer satisfaction, ASAAS offers immersive experiences for various industries, including schools, hotels, museums, and healthcare facilities, and aims to elevate online presence through innovative virtual solutions.

📋 Description

• Lead the architecture design of the real-time ML platform, evaluating alternatives and driving technical decisions • Deliver the platform as a service, with standards, interfaces, and documentation that enable data science and product teams to independently define, deploy, and consume features and models • Build and evolve the online and offline feature store, with cataloged metadata • Build and evolve model registry and versioning capabilities • Build and evolve real-time inference capabilities • Build and evolve production model monitoring • Ensure consistency between features used for training and inference, using the same logic in batch and streaming • Define requirements with engineering teams responsible for event flows • Integrate the platform with AWS ML services, using Amazon SageMaker for feature storage, model registry, and real-time inference • Structure the operation of the platform and production models with Cloud and Data Platform teams, using IaC, standards, and runbooks • Ensure latency, availability, and scalability through SLOs and observability • Document technical decisions, standards, and operational procedures

🎯 Requirements

• Production experience with real-time machine learning models, event-triggered inference, and low-latency requirements • Experience delivering platforms as a service, with self-service architecture standards, documentation, and interfaces that enable science and product teams to work autonomously • Experience building online and offline Feature Stores with cataloged metadata • Experience ensuring consistency between training and inference • Hands-on experience structuring model registries and versioning, such as MLflow • Experience monitoring models in production • Experience building data and ML platforms on AWS, preferably with Amazon SageMaker or equivalent services • Advanced proficiency in Python and SQL • Advanced proficiency in Terraform (IaC) • Experience automating deployments through CI/CD • Experience with production observability • Nice to have: experience with financial products and real-time decision-making • Nice to have: knowledge of Kafka, Kinesis, CDC, AWS DMS, or MSK • Nice to have: experience with the Databricks ecosystem • Nice to have: knowledge of Brazil’s LGPD, Central Bank of Brazil (BACEN) regulations, and SOX

🏖️ Benefits

• Medical and dental insurance with no copayments • Life insurance • Prescription drug assistance • Fitness allowance • Four free therapy or nutritionist sessions per month • Quick massage at headquarters • Flexible meal benefit on a Visa card • Free food at headquarters • Childcare assistance • Parental support program • Extended maternity and paternity leave • In-house training platform • Education assistance covering 70% of undergraduate tuition and language courses, as well as courses and books • Home office allowance • Work equipment • Home office furniture allowance • Partnership with WOBA for access to coworking spaces throughout Brazil • Birthday month day off • Happy hour allowance • Referral bonus for new hires • Bonus based on annual goals • Stock option plan • No dress code

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