Pessoa Cientista de Dados Sênior in Brazil, Indiana at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Pessoa Cientista de Dados Sênior based in Brazil.

This role focuses on developing advanced Artificial Intelligence and Machine Learning solutions that create measurable business impact. You will act as a technical reference in Data Science, with a strong focus on Natural Language Processing (NLP) and Large Language Models (LLMs). The position combines research, engineering, and product collaboration to transform complex challenges into scalable AI solutions. You will design and maintain data and machine learning pipelines, ensuring reliability, performance, and production readiness. Working in a collaborative and innovation-driven environment, you will partner with engineering, product, and business teams to deliver cutting-edge technology. The ideal candidate brings deep technical expertise, curiosity, and a passion for building impactful AI systems.

• Act as a technical reference in Machine Learning and Artificial Intelligence, supporting technical and product decisions with expertise in NLP and Large Language Models.
• Design, implement, and maintain data and machine learning pipelines covering model training, evaluation, deployment, and inference processes.
• Develop scalable and reliable AI solutions focused on performance, quality, and measurable business outcomes.
• Apply traditional Machine Learning techniques alongside modern AI approaches to solve complex business challenges.
• Research, propose, and implement innovative solutions involving NLP, LLMs, cloud technologies, and advanced AI architectures.
• Collaborate closely with product, engineering, and business teams to translate business challenges into effective AI solutions.
• Ensure AI and ML deliveries follow modern engineering practices, including scalability, observability, reliability, and production readiness.
• Support the evolution of AI capabilities through continuous improvement of models, processes, and technical approaches.
• Work with large-scale data environments and distributed processing solutions to enable robust AI applications.

• Advanced proficiency in Python and experience with major Machine Learning libraries such as Scikit-learn, TensorFlow, PyTorch, or similar technologies.
• Strong practical experience with Natural Language Processing (NLP) and Large Language Models (LLMs).
• Solid understanding of data and ML pipeline architecture, including training, evaluation, deployment, and inference workflows.
• Experience using cloud platforms, particularly AWS, for data processing and model deployment.
• Knowledge of modern Machine Learning Engineering and AI production practices.
• Experience working with Big Data and distributed processing technologies such as Spark, including batch and streaming pipelines.
• Hands-on experience with MLOps and/or LLMOps practices, including experiment tracking, model registries, observability, monitoring, and model drift detection.
• Ability to design scalable, reliable, and maintainable AI solutions in production environments.
• Strong problem-solving skills, analytical thinking, and ability to collaborate across technical and business teams.
• Experience with advanced ML/AI monitoring and observability solutions is a plus.
• Experience integrating generative AI approaches with traditional Machine Learning models is highly valued.
• Knowledge of distributed systems strategies such as replication and caching is desirable.
• Experience with Retrieval-Augmented Generation (RAG) and vector databases such as pgvector, OpenSearch, Pinecone, or FAISS is a plus.
• Familiarity with Big Data and Analytics ecosystems, including Databricks, EMR, Kafka, or Kinesis, as well as AI workload cost optimization practices, is advantageous.
• Experience developing AI agent solutions for large-scale data processing and analysis is a differentiator.

• Fully remote work model with the flexibility to work from anywhere.
• Flexible working hours focused on autonomy and responsibility.
• Education assistance and professional development support.
• Internal career development tools, guilds, and study groups.
• Health insurance and dental insurance coverage.
• 24/7 telemedicine access.
• Free online therapy support.
• Access to Wellhub wellness programs.
• Extended maternity and paternity leave.
• Employee support center for professional and personal assistance.
• Meal and food allowance.
• Life insurance.
• Transportation allowance.
• Home office assistance.
• Childcare assistance.
• Mobile phone allowance.
• Profit-sharing program.