Pelo Futuro da Indústria | Pelo Futuro do Trabalho
Doctoral Research Fellow – LLM, Model Evaluation, Python, Prompt Engineering
Location
Brazil
Posted
3 days ago
Salary
R$11K / month
Seniority
Senior
Job Description
Doctoral Research Fellow – LLM, Model Evaluation, Python, Prompt Engineering
Sistema Fibra
• Design and implement evaluations and tests of synthetic personas to simulate different user profiles, goals, and behaviors • Develop experimental LLM-as-a-Judge pipelines, including prompt engineering, rubric design, and automated evaluation protocols for scalable analysis of AI-generated responses • Combine concepts from Reinforcement Learning and Preference Optimization • Research and apply preference optimization techniques and reinforcement learning to continuously improve language models, analyzing impacts on quality, robustness, and alignment
Job Requirements
- Education: PhD
- Fields of study: Computer Science, Computer Engineering, Information Systems, Data Science, Statistics, Applied Mathematics, or related areas in Computing, Artificial Intelligence, or Machine Learning
- Programming: Python
- Knowledge of Machine Learning and Deep Learning fundamentals
- Familiarity with Large Language Models (LLMs) and Generative AI
- Experience with AI model development libraries (PyTorch and/or Hugging Face Transformers)
- Ability to read and comprehend scientific papers in English
- Basic knowledge of experimental design, results analysis, and model evaluation
- Experience with LLM evaluation / LLM-as-a-Judge (a plus)
- Experience with RLHF, DPO, or preference optimization (a plus)
- Participation in scientific research/publications in AI or Machine Learning (a plus)
- Experience with code agents (Claude Code, GitHub Copilot, Codex, etc.) (a plus)
Benefits
- Stipend: R$ 11,000.00
- Remote work
Related Guides
Related Job Pages
More Backend Engineer Jobs
Role Description We are seeking an experienced Golang Developer to design and build high-performance backend services, infrastructure tooling, and cloud-native applications using Go. In this role you will work on systems where latency, concurrency, and operational efficiency are first-class concerns, and you will contribute to a codebase shared by engineers across multiple teams. The ideal candidate will combine strong Go expertise with broad systems knowledge, including network programming, container ecosystems, and distributed system design. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production. Qualifications - Bachelor’s degree in Computer Science, Engineering, or a related technical discipline. - Five or more years of professional software engineering experience, with significant time in Go. - Strong understanding of Go concurrency patterns (goroutines, channels, contexts). - Hands-on experience building production gRPC and/or REST APIs in Go. - Experience with Kubernetes-native development (client-go, controller-runtime). - Solid experience with relational and key-value data stores. - Strong understanding of distributed systems and networking fundamentals. - Experience with CI/CD pipelines and container-based deployment. - Excellent debugging and performance-engineering skills. - Strong communication and documentation skills. Requirements - Design and implement performant backend services and APIs in Go, with strong attention to concurrency, error handling, and resource management. - Build cloud-native applications using Go and Kubernetes-native libraries, applying idiomatic Go patterns, well-defined module boundaries, and operational hooks that make the resulting services easy to deploy and run. - Develop CLI tools, Kubernetes controllers, and custom operators for internal platforms, designing clear command surfaces, robust error handling, and reconciliation logic that operates safely in long-running environments. - Implement gRPC and REST APIs with appropriate observability and security. - Profile and optimize Go applications for memory, GC, and goroutine behavior, applying systematic measurement, targeted improvements, and data-driven validation to deliver quantifiable gains in throughput, latency, or resource efficiency. - Integrate with messaging systems (Kafka, NATS) and data stores (PostgreSQL, Redis, etcd). - Build comprehensive automated tests, including unit, integration, and benchmark tests. - Implement structured logging, metrics emission, and distributed tracing throughout services so that operators and on-call engineers have the signals they need to diagnose issues and reason about system behavior. - Lead code reviews and uphold engineering standards in Go projects. - Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time. - Contribute meaningfully to internal Go libraries, shared platform tooling, and reusable patterns that accelerate development across multiple engineering teams and codify hard-won best practices. - Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time. - Continuously evaluate Go ecosystem evolution and contribute to internal patterns. Benefits - Competitive base salary commensurate with experience, plus benefits. - Long-term, multi-year engagement aligned to the Bright Vision SOW delivery roadmap. - 100% remote work opportunity.
Senior Python GenAI Engineer
EPAM SystemsEPAM Systems is an information technology (IT) company that has become a leading global digital and product design, digital platform engineering, and product de
Senior Python GenAI Engineer Location: Remote in Türkiye Job Description: We are looking for a highly skilled Senior Python Engineer to join a fast-paced, innovative team working on modern data platforms and AI-driven solutions. You will play a key role in designing scalable data pipelines, building cloud-native applications, and leveraging GenAI tools to accelerate development. Responsibilities - Design and develop scalable web services and background jobs using FastAPI - Build and optimize data processing and reporting solutions - Develop and maintain robust data pipelines and architectures - Work with modern cloud platforms (primarily Azure) to deploy and manage applications - Implement CI/CD pipelines and automation processes - Apply Infrastructure as Code (IaC) practices for scalable environments - Leverage AI-assisted development tools (e.g., Copilot) for spec-driven development Requirements - Strong Python experience (5+ years in production) - Hands-on experience with web frameworks (FastAPI preferred) - Experience with data processing tools: Pandas, Polars, openpyxl, DuckDB - Solid understanding of data pipeline design (data lakes, medallion architecture, star schema) - Experience with CI/CD tools (e.g., GitHub Actions) - Experience with Azure services (Container Apps, Storage, Service Bus, SignalR) - Experience with IaC tools (Bicep, Terraform, or AWS CDK) - Familiarity with AI-assisted development tools (e.g., GitHub Copilot) Nice to have - Experience with Airflow, dbt, Streamlit - Distributed systems and async workflows - Enterprise messaging patterns - Experience with Snowflake (stored procedures, streams, tasks, pipes, time travel) - .NET Core experience (legacy systems support) - Frontend experience (Angular or Next.js) We offer/Benefits CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT - Diversity of assignments and projects - Personal development plan - Mentoring programs and leadership development - Certification and professional development support - Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses - English courses taught by certified teachers CORPORATE BENEFITS - Extra leave days - Referral bonuses COMPENSATION PACKAGE - Competitive compensation paid in USD - Regular salary and performance reviews MEDICAL & HEALTHCARE - Private health insurance WORKING ENVIRONMENT - Recreation office zones with tea, coffee and snacks - Sports and game consoles - IT equipment and Microsoft's Software Assurance Home Use Program (HUP)
• Building and shipping full‑stack features end‑to‑end with a strong focus on customer outcomes. • Designing and delivering cloud‑native solutions using Azure Functions and event‑driven patterns. • Using AI to accelerate discovery, solution design, implementation and testing while keeping quality, security and maintainability front of mind. • Creating reliable delivery flows with Azure DevOps and GitHub Actions, including strong validation and release discipline. • Turning business needs into clear delivery slices, acceptance criteria and prioritised backlog items. • Collaborating directly with clients and internal teams to validate ideas quickly and deliver meaningful value
• Design and develop scalable, fault-tolerant backend services following Microservices and Hexagonal Architecture principles. • Deploy and manage containerized applications on Azure Kubernetes Service (AKS) using Docker and Azure-native infrastructure. • Collaborate with Product and Engineering teams to translate business requirements into scalable technical solutions. • Create architecture documentation, estimations, and user stories that support Agile delivery processes. • Ensure platform performance, security, reliability, and SLA compliance through engineering best practices. • Mentor and guide engineers while promoting ownership, quality, and technical excellence. • Lead and participate in code reviews to ensure scalability, maintainability, and adherence to engineering standards. • Contribute to observability, incident response, and continuous platform improvement initiatives. • Influence technical roadmaps and contribute to architecture, tooling, and platform decisions. • Support operational excellence initiatives across backend systems and cloud environments.



