Scrum Master jobs in Brazil

Job Title:

Engineering & Computer Science Subject Matter Expert – AI Training & Content Development

About Innodata:

Innodata (NASDAQ: INOD) is a global leader in data engineering and AI-powered solutions , partnering with 4 of the world’s top 5 technology companies and serving over 2,000 enterprise clients worldwide . With a workforce of 5,000+ subject matter experts and operations in 13 cities globally , Innodata is at the forefront of Machine Learning (ML), Natural Language Processing (NLP), and Large Language Model (LLM) development.

We combine deep domain expertise, advanced AI/ML capabilities, and high-security infrastructure to build next-generation AI systems that are more intelligent, context-aware, and safe.

About the Role:

We are seeking highly skilled Engineering & Computer Science Subject Matter Experts (SMEs) with exceptional technical expertise, research ability, and content creation skills to join our AI/LLM training team.

In this role, you will design, curate, and review technical content that enhances AI’s understanding of engineering disciplines, computing systems, algorithms, software engineering principles, and applied technologies. Your expertise will directly shape how AI systems reason about, solve, and communicate engineering and computer science concepts .

Key Responsibilities:

Content Development:

• Create high-quality technical content , including:
• Problem-solving exercises and step-by-step solutions.
• Theoretical and applied engineering summaries.
• Software design patterns, coding best practices, and algorithm explanations.
• Technical documentation, system architecture diagrams, and engineering principles.
• Cover multiple domains, including (but not limited to):
• Engineering: Electrical, Mechanical, Civil, Industrial, Systems, and Robotics.
• Computer Science: Data Structures, Algorithms, Operating Systems, Computer Architecture, Cybersecurity, and AI/ML.
• Software Engineering: Full-stack development, DevOps, Cloud Computing, Databases, and Distributed Systems.
• Review AI-generated responses to complex technical questions for accuracy and completeness.
• Identify and correct conceptual gaps, computational errors, and ambiguous phrasing .
• Develop evaluation rubrics to improve reasoning and problem-solving capabilities in AI.

Research & Technical Collaboration:

• Collaborate with engineers, computational linguists, and AI researchers to refine datasets and model performance.
• Contribute insights on systems engineering principles, optimization, and software development lifecycles .
• Support AI ethics and safety efforts to ensure responsible deployment of technical knowledge.

Eligibility Criteria:

• Master’s or PhD in Engineering, Computer Science, Software Engineering, or related STEM field .
• Strong foundation in:
• Computer Science Concepts (Algorithms, Data Structures, Computational Complexity, etc.)
• Software Development Practices (Agile, DevOps, CI/CD).
• Demonstrated expertise in technical writing, curriculum development, or advanced R&D projects .

Preferred Skills:

• Familiarity with ML, NLP, and LLMs (a plus).
• Hands-on experience with Python, C++, Java, or similar programming languages .
• Knowledge of distributed systems, cloud computing, and cybersecurity fundamentals .
• Strong ability to simplify complex concepts for varied audiences.

Why Join Innodata?

• Influence AI reasoning in engineering and computing at a global scale.
• Work with world-class researchers, linguists, and technologists .
• Contribute to cutting-edge AI development shaping industries worldwide.
• Remote-first, flexible work arrangements and research-driven culture .

Additional Information:

• Candidates must complete an English Language Assessment .
• This step is mandatory and non-billable.

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider of choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.

Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel, and Germany. We’re poised for a period of explosive growth over the next few years.

About the Role:

At Innodata, we’re working with the world’s largest technology companies on the next generation of generative AI and large language models (LLMs). We’re looking for smart, savvy, and curious subject matter experts.

We are seeking a Medical Writer Subject Matter Expert with exceptional writing and analytical skills to join our AI/ML data team. In this role, you will help train advanced Large Language Models (LLMs) by producing, curating, and reviewing high-quality medical and scientific content. Your expertise will directly shape the way AI systems understand, explain, and communicate clinical and biomedical information.

Key Responsibilities:

Create high-quality, accurate, and medically sound content, including:

• Clinical and scientific explanations of medical topics
• Research summaries, clinical abstracts, and literature reviews
• Medical problem sets, case studies, and evidence-based Q&A
• Regulatory, pharmacological, or public health-focused content (as applicable)

Collaborate with AI researchers and engineers to:

• Review and refine medical-related model outputs
• Identify and address conceptual gaps in LLM training data
• Build diverse datasets across medical and healthcare domains (e.g., anatomy, pathology, pharmacology, public health, epidemiology, evidence-based medicine)
• Provide feedback to improve LLM performance in reasoning, comprehension, and communication of healthcare content

Eligibility Criteria:

• Master’s degree or PhD in Medicine, Biomedical Sciences, Pharmacy, Public Health, or a related healthcare/clinical discipline
• (Exceptional candidates with professional degrees such as MD, DO, PharmD, MPH, or equivalent clinical experience will be considered)
• Strong background in medical/scientific writing, with the ability to communicate complex topics clearly and accurately
• Experience with literature review, evidence synthesis, or regulatory writing is a plus
• Familiarity with scientific publishing standards, citation practices, and biomedical databases (e.g., PubMed, Cochrane)

Additional Requirement:

As part of the project, you are required to complete the English language assessment.

This assessment is mandatory and non-billable.

Job Title:

Physics Subject Matter Expert – AI Training & Content Development

About Innodata:

Innodata (NASDAQ: INOD) is a global leader in data engineering and AI-powered solutions , working with 4 of the top 5 global technology companies and over 2,000 enterprise clients worldwide . Operating in 13 global locations with a workforce of 5,000+ subject matter experts , Innodata leads innovation in machine learning (ML), natural language processing (NLP), and large language model (LLM) training.

By combining cutting-edge AI technology, deep domain expertise, and secure infrastructure , Innodata delivers transformative solutions that power the next generation of intelligent systems.

About the Role:

We are seeking a Physics Subject Matter Expert (SME) with exceptional analytical, problem-solving, and writing skills to join our AI/LLM training team .

You will play a crucial role in developing, curating, and evaluating advanced physics content to enhance AI models’ reasoning, accuracy, and ability to explain complex physics concepts.

This role is ideal for physicists, researchers, and academics passionate about science communication and AI innovation.

Key Responsibilities:

Content Development:

• Create high-quality physics datasets , including:
• Conceptual explanations of physics principles (classical, quantum, and modern physics).
• Problem sets and numerical solutions.
• Detailed derivations of equations and laws.
• Technical summaries and scientific research briefs.
• Build domain-specific datasets across physics subfields such as:
• Mechanics, Thermodynamics, and Electromagnetism
• Quantum Mechanics, Particle Physics, and Nuclear Physics
• Astrophysics, Relativity, and Cosmology
• Materials Science and Condensed Matter Physics
• Computational Physics and Applied Physics
• Evaluate LLM-generated physics content for accuracy, clarity, rigor, and logical reasoning.
• Detect and correct conceptual gaps, numerical errors, and inconsistencies in AI outputs.
• Help define data quality standards and evaluation rubrics for scientific reasoning.
• Work closely with AI engineers, computational linguists, and data scientists to improve AI reasoning.
• Provide domain expertise for designing AI benchmarks and test scenarios.
• Contribute to research on physics education, simulation modeling, and AI-assisted scientific research.

Eligibility Criteria:

• Master’s or PhD in Physics, Applied Physics, Engineering Physics, or a related discipline (PhD preferred).
• Strong foundation in theoretical and applied physics .
• Demonstrated expertise in one or more areas:
• Computational modeling, simulations, or numerical methods.
• Advanced topics (e.g., quantum field theory, condensed matter, astrophysics).
• Proven experience in academic publishing, science communication, or curriculum design .
• Strong technical writing skills and ability to explain complex concepts clearly .

Preferred Skills:

• Familiarity with AI/ML models, data annotation, and prompt engineering (bonus).
• Experience in LaTeX, Python, or scientific computing tools .
• Knowledge of AI fairness and bias detection in STEM datasets.

Why Join Innodata?

• Shape the future of AI by embedding physics expertise into large-scale models.
• Collaborate with top-tier researchers and engineers globally.
• Influence next-gen AI capabilities in scientific reasoning.
• Work remotely with flexibility and innovation-driven teams .

Additional Information:

• Candidates must complete an English Language Assessment .
• Mandatory and non-billable step.

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider of choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.

Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.

About the Role:

At Innodata, we’re working with the world’s largest technology companies on the next generation of generative AI and large language models (LLMs). We’re looking for smart, savvy, and curious subject matter experts.

We are seeking a Mathematics Subject Matter Expert with exceptional writing and analytical skills to join our AI/ML data team. In this role, you will help train advanced Large Language Models (LLMs) by producing, curating, and reviewing high-quality educational and technical mathematics content. Your expertise will directly shape the way AI systems understand, explain, and reason about fundamental and advanced mathematical concepts.

Key Responsibilities:

Create high-quality, accurate, and pedagogically sound content in mathematics, including:

• Conceptual explanations
• Problem sets and solutions
• Theoretical summaries and derivations
• Research abstracts and technical writing

Collaborate with AI researchers and engineers to:

• Review and refine mathematics-related model outputs
• Identify and fill conceptual gaps in LLM training data
• Build datasets across various mathematics domains (e.g., Algebra, Calculus, Geometry, Linear Algebra, Probability, Statistics, Number Theory, Discrete Math, etc.)
• Provide feedback to improve LLM performance in reasoning, solving, and communicating mathematical content

Eligibility Criteria:

• Master's or PhD in Mathematics or a closely related discipline (MS with exceptional experience may be considered)
• Strong background in theoretical and/or applied mathematics
• Excellent technical and academic writing skills

As part of the project, you are required to complete the English language assessment.

*The assessment is mandatory & non-billable*

Job Title:

Biological & Biomedical Sciences / Chemistry Subject Matter Expert – AI Training & Content Development

About Innodata:

Innodata (NASDAQ: INOD) is a global leader in data engineering and AI-powered technology solutions , trusted by 2,000+ enterprise customers worldwide, including 4 of the top 5 global technology companies . With operations in 13 cities and a workforce of over 5,000 experts across the United States, Canada, the UK, the Philippines, India, Sri Lanka, Israel, and Germany , Innodata is at the forefront of artificial intelligence (AI), natural language processing (NLP), and large language model (LLM) innovation.

We combine cutting-edge ML/AI technologies , deep scientific expertise , and high-security infrastructure to deliver next-generation solutions for industries spanning pharma, life sciences, healthcare, technology, finance, and law.

About the Role:

We are seeking Subject Matter Experts (SMEs) in Biological & Biomedical Sciences and Chemistry to join our AI/ML model training and content development team. In this role, you will leverage your scientific expertise to curate, validate, and create domain-specific content that improves AI reasoning, knowledge representation, and performance in life sciences and chemical sciences.

You will directly contribute to the training of advanced LLMs and scientific AI systems by developing datasets, reviewing model outputs, and ensuring alignment with scientific accuracy, regulatory compliance, and ethical standards.

Key Responsibilities:

• Develop scientifically accurate, domain-rich datasets in:
• Molecular Biology, Biochemistry, and Genetics
• Pharmacology and Biomedical Engineering
• Cell and Developmental Biology, Immunology, Microbiology
• Biotechnology, Toxicology, and Chemical Engineering
• Produce high-quality scientific content, including:
• Research abstracts and technical white papers
• Standard operating procedures (SOPs)
• Analytical chemistry workflows and chemical reaction mechanisms
• Biomedical case studies, drug development datasets, and molecular pathway analyses
• Validate AI-generated outputs for accuracy, reproducibility, and compliance with scientific and safety standards.
• Identify and correct conceptual errors, dataset biases, or incomplete knowledge representations.
• Contribute to knowledge graph development and ontology engineering for biological and chemical datasets.

Cross-Disciplinary Collaboration:

• Collaborate with AI engineers, data scientists, and computational chemists to optimize model reasoning.
• Support the creation of adversarial testing datasets for LLMs in biomedical and chemical domains.
• Participate in R&D discussions to enhance AI performance in drug discovery, materials science, and biomedical research applications.

Eligibility Criteria:

• Advanced degree required : Master’s, PhD, or equivalent in Biology, Biomedical Sciences, Chemistry, Biochemistry, Molecular Biology, Chemical Engineering, or a related field.
• Strong expertise in laboratory research, computational modeling, bioinformatics, or chemical analysis.
• Proven experience in scientific writing, peer-reviewed publication, or technical documentation.
• Familiarity with regulatory frameworks, laboratory safety, and ethical research guidelines.
• Preferred experience with:
• Computational chemistry, cheminformatics, or molecular modeling software.
• Bioinformatics pipelines, omics data analysis, and high-throughput screening methodologies.

Additional Information:

• Selected candidates must complete an English Language Assessment.
• Mandatory and non-billable step.