Staff ML Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 10%

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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Hand Talk

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

📚 Education

🌍 Social Impact

💰 $670k Seed Round on 2018-08

Education • Social Impact • Technology

Hand Talk is the largest Sign Language translation platform in the world, designed to enhance communication for deaf individuals. The platform, which includes a mobile app, offers tools for learning and translating Sign Languages such as ASL and Libras, promoting accessibility and inclusion in various environments. Awarded by the UN as the 'best social app in the world,' Hand Talk serves as a vital resource for individuals and businesses seeking to bridge communication gaps with the deaf community.

📋 Description

• Partner with ML researchers on generative AI teams to identify bottlenecks and improve the speed, scalability, and reliability of research iteration • Design, build, and maintain reusable research infrastructure, workflows, models, interfaces, and automation for experimentation, training, evaluation, data processing, and model packaging • Enable reproducible experiments through consistent environments, dependency management, artifact and model versioning, configuration, observability, and CI/CD practices • Support scalable ML workloads involving large datasets, GPU clusters, distributed computing, and multiple interconnected models, services, and algorithmic components • Deliver pragmatic research-support capabilities aligned with the architecture and roadmap of the core ML platform • Serve as a technical bridge between researchers and the ML platform team by translating pain points into clear requirements, validating capabilities, and helping drive adoption of the shared platform • Collaborate to improve the path from research to product by making results easier to reproduce, integrate, and test • Contribute to shared ML engineering standards and architecture, and promote engineering practices through hands-on collaboration, technical guidance, and knowledge sharing • Evaluate and introduce technologies that improve the speed, reliability, scalability, and cost efficiency of research

🎯 Requirements

• Proven experience building reusable infrastructure, tools, or developer platforms for multiple engineers or researchers • Strong proficiency in Python and Linux • Hands-on experience with Docker, Kubernetes, CI/CD pipelines, AWS, and Infrastructure as Code, such as Terraform • Practical understanding of the end-to-end ML lifecycle, including data preparation, experimentation, training, evaluation, model and artifact management, packaging, deployment, and monitoring • Experience with compute-intensive or distributed workloads, including diagnosing reliability, performance, resource, and cost bottlenecks • Practical knowledge of modern ML frameworks, such as PyTorch • Ability to work with ambiguous and evolving requirements and turn them into reusable engineering capabilities • Strong communication and cross-functional collaboration skills across research, engineering, and platform teams • Advanced English required — conversational, written, and reading proficiency • Interest in diversity, inclusion, and accessibility • Curiosity • Collaborative mindset • Structured and action-oriented approach • Comfortable working in ambiguity and early-stage environments • Impact-focused • Nice to have: experience in language modeling, language translation, computer vision, multimodal or generative AI, robotics, and autonomous systems • Nice to have: experience scaling GPU clusters, distributed computing, and large-scale data processing • Nice to have: experience building researcher-facing ML platforms and self-service experimentation environments • Nice to have: experience helping research teams migrate to or adopt a shared ML platform • Nice to have: knowledge of inference optimization techniques, such as custom GPU kernels

🏖️ Benefits

• CLT employment contract: Security and all legally guaranteed employment rights from day one. • Caju Benefits Card (R$1,160.00): Flexibility to use your balance as you prefer—for meals, groceries, home office, culture, and transportation. • Remote work from anywhere in Brazil • SulAmérica Health Insurance • SulAmérica Dental Insurance • SulAmérica Life Insurance • Online specialist consultations through Conexa Saúde telemedicine • Wellhub • Extended year-end break • Birthday day off • Extended parental leave • Ongoing professional development through LinkedIn Learning • Annual stipend for courses and professional training • University partnerships • Brazilian Sign Language (Libras) training • English Pass • Work equipment shipped as part of the onboarding kit