Senior Machine Learning Engineer at Itaú, driving innovation with data and AI solutions. Collaborating across teams to implement robust machine learning architectures and ensure scalable deployments.
About the role
- Software Engineer managing cloud infrastructure and ML model implementations for FactSet. Collaborating with engineers to support and deliver AI solutions.
Responsibilities
- Manage and deploy various cloud-based infrastructure
- Develop a roadmap for management and growth of existing pipelines and infrastructure for serving ML and AI solutions
- Deployment and maintenance of models, databases, and applications
- Support work on various AI/ML projects including entity and topic modeling, semantic tagging/enrichment, information extraction, transfer learning, and graph neural networks
- Develop dashboards and visualizations for financial experts
- Ingest and analyse structured and unstructured data
- Develop processes for data collection, quality assessment, and quality control
- Keep up to date with state-of-the-art approaches and technological advancement
- Collaborate with other Engineering teams
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning or a related field
- 3 + years of working experience as a Software Engineer/ Machine Learning Engineer
- Experience with cloud-based infrastructure (AWS preferred)
- Familiarity with ML, NLP and GenAI (including RAG, Prompt Engineering, Vector DBs)
- Successful history of writing production grade code and releasing in an enterprise environment
- Team player
- Fluent in English; ability to communicate about complex subjects to non-technical stakeholders
- Highly proficient in Python
- Experience with OpenAI, Anthropic, and other large language models.
- Prior experience working with unstructured data (text content, JSON records)
- Working with Agile development practices in a production environment
- Experience with AWS environment [SageMaker, S3, Athena, Glue, ECS, EC2]
- Experience with Agentic workflows and MCP
- Experience working with large volumes of data in a stream or batch processing environment.
- Prior experience with Docker and API development.
- Usage of MongoDB
- Familiarity with deep learning libraries (Keras, PyTorch, Tensorflow)
- Familiarity with big data tool chain (e.g. Pyspark, Hive)
- Experience with information extraction, parsing and segmentation
- Knowledge of ontologies, taxonomy resolution and disambiguation.
- Experience in Unsupervised Learning techniques Density Estimation, Clustering and Topic Modelling.
- Graph database experience (AWS Neptune, Neo4j)
Benefits
- Flexible working hours
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Machine Learning Engineer responsible for developing and deploying advanced ML and AI solutions at Zendesk. Collaborating with stakeholders to deliver impactful business outcomes using latest machine learning technologies.
Lead advanced machine learning model development and optimization at PayPal. Collaborate with teams to deploy scalable ML solutions in production environments.
Senior Machine Learning Engineer at Pivotal Health developing ML systems for healthcare reimbursement. Collaborating across teams to build and maintain reliable, production - grade machine learning systems.
Machine Learning Engineer working with Algorithm team on customer onboarding processes. Focus on execution and automation of models using computer vision and AI in sports industry.
Senior Machine Learning Engineer at Troveo designing and optimizing machine learning pipelines for AI video models. Collaborating with cross - functional teams to build scalable video data solutions.
AI/ML Engineer developing AI systems for data security at Nightfall. Collaborating with engineers and contributing to AI features.
Internship in cheminformatics and machine learning at Genesis Molecular AI, driving drug discovery projects and improving internal tools.
Software Engineer focusing on ML infrastructure for drug discovery at Genesis AI. Leading engineering efforts to enhance scalable platforms for generative modeling and large - scale simulations.
AI/ML Engineer developing machine learning systems for TymeX's digital banking platform. Collaborating across teams to enhance customer interaction and personalization through AI technology.