AI Research Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI Research Engineer based in Brazil.

This is an opportunity to contribute to advanced AI research initiatives by designing experiments, improving models, and developing innovative machine learning solutions.
You will work on challenging research problems involving large language models, natural language processing, and data-centric AI methodologies.
The role combines theoretical expertise with hands-on engineering to transform research ideas into practical outcomes.
You will independently own research projects while collaborating with multidisciplinary teams focused on AI innovation.
This position offers the chance to influence model evaluation, training approaches, and the future of intelligent systems.
You will join a remote-first environment where experimentation, technical excellence, and impactful research are highly valued.

Accountabilities:

• Independently own and execute AI research tasks or sub-projects, delivering high-quality experimental results and meaningful contributions to research initiatives.
• Design and implement complex experiments to validate hypotheses, define evaluation protocols, and compare model performance against relevant benchmarks.
• Analyze research outcomes, interpret results, and communicate clear conclusions and recommendations.
• Develop high-quality, reusable code contributions for machine learning research repositories and reference implementations.
• Improve internal benchmarks by identifying data gaps, proposing evaluation metrics, and introducing new models or comparison methods.
• Create data-driven research workflows to improve model training, evaluation, and performance measurement.
• Design and optimize pipelines for evaluating large language models, including quality, safety, faithfulness, coherence, and reasoning capabilities.
• Collaborate with technical and non-technical stakeholders by translating complex AI concepts into clear guidelines and actionable insights.
• Conduct controlled experiments, ablation studies, and adversarial testing to understand model behavior and improve reliability.
• Contribute to the development of scalable AI research practices through automation, documentation, and engineering excellence.

Requirements:

• PhD or Master’s degree in Computer Science, Computational Linguistics, Machine Learning, or a related quantitative field.
• 3+ years of hands-on experience in applied NLP research, machine learning engineering, AI research labs, or data-centric AI environments.
• Strong theoretical and practical knowledge of Transformer architectures, including GPT-style decoder models, encoder-decoder architectures, attention mechanisms, positional embeddings, and tokenization techniques such as BPE or SentencePiece.
• Extensive experience with post-training methods, including Supervised Fine-Tuning (SFT), RLHF, PPO, and Direct Preference Optimization (DPO).
• Experience working with large-scale datasets, noisy label handling, data annotation strategies, active learning, and semantic bias analysis.
• Knowledge of LLM evaluation approaches, including LLM-as-a-Judge pipelines, pairwise comparison systems, and reference-free metrics.
• Understanding of AI agent evaluation, including function/tool calling, ReAct frameworks, and reasoning trajectory assessment.
• Experience designing data evolution pipelines, knowledge distillation techniques, and approaches to reduce model collapse from synthetic data.
• Familiarity with adversarial testing, safety evaluation, prompt stress testing, and balancing helpfulness with model safety.
• Expert-level Python skills and strong experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Ability to process and manage large-scale text datasets using scripting, JSONL manipulation, regular expressions, and data optimization techniques.
• Experience with data versioning tools such as DVC or LakeFS is a plus.
• Strong analytical thinking, research communication skills, and ability to work effectively in ambiguous environments.

Benefits:

• Fully remote work opportunity for candidates based in Brazil.
• Flexible work arrangements with opportunities for eligible candidates to access office locations.
• Opportunity to contribute to cutting-edge AI research and large-scale machine learning projects.
• Exposure to advanced technologies in NLP, generative AI, model evaluation, and data engineering.
• Collaboration with global teams of AI researchers, engineers, and technical specialists.
• Opportunity to influence the development of innovative AI systems and research methodologies.
• Professional growth through complex research challenges and continuous learning opportunities.
• Inclusive and collaborative environment focused on innovation, diversity, and technical excellence.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1