Brazil onlyWe are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry.
Job Duties
We are seeking a Back-end Developer with strong programming skills and a solid foundation in scientific computing to build and optimize data-driven applications. In this role, you will design and implement robust backend systems that process and analyze complex datasets, enabling advanced analytics and real-time insights.
You will collaborate with cross-functional teams to deliver scalable, high-performance solutions that support research and innovation in a dynamic environment.
Key Responsibilities
- Develop and maintain end-to-end applications, including back-end services in Python
- Collaborate with cross-functional teams to design and deliver scalable, high-quality solutions
- Optimize and refactor existing code for performance and scalability
- Troubleshoot, debug, and resolve issues in applications and systems
- Stay current with trends in full-stack development, data visualization, and cloud technologies
- Maintain strong knowledge of modern development tools, standards, and best practices
Qualifications
- Bachelor's degree in computer science, engineering, or a related technical field
- 4+ years of professional software development experience (preferred)
- Strong proficiency in Python programming
- Hands-on experience with NumPy and Pandas
- Familiarity with back-end frameworks (e.g., FastAPI, Django) is a plus
- Strong understanding of data structures, algorithms, and statistical analysis
- Strong debugging, problem-solving, and analytical skills
- Ability to work independently and collaboratively in a fast-paced environment
- Strong communication skills in English (written and verbal)
Knowledge, Skills, and Abilities
- Master's degree in computer science, engineering, or a related technical field
- Optimization & Uncertainty Quantification: Strong knowledge on platforms for DOE, Bayesian optimization, surrogate modeling, sensitivity analysis, and robust optimization under uncertainty
- Agentic AI & LLM Integration: Ability to design workflows using LLMs for experiment planning, tool orchestration, and explainable recommendations, including prompt engineering and safety guardrails.
- Experience in the Oil & Gas industry (nice to have)
- Experience with machine learning frameworks (TensorFlow, Scikit-learn)
- Knowledge of SQL/NoSQL databases and query development
- Experience working in Agile/Scrum development environments
- Solid understanding of data structures, algorithms, and statistical analysis
- Knowledge of REST APIs and microservices architecture
- Proficiency with Git and version-control best practices
- Excellent analytical, debugging, and problem-solving skills
- Ability to work independently and collaboratively in a fast-paced environment
- Strong communication skills in English (written and verbal)
Nice to Have
- Reservoir Simulation Expertise: Hands-on experience with compositional simulation, including case setup, input/output parsing, and history matching integration
- Cloud/HPC Computing: Familiarity with scheduling, parallel runs, resource optimization on HPC clusters or cloud platforms (Azure/AWS/GCP)
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location
Fully remote position.
Job Details
Requisition Number: 205558
Experience Level: Entry-Level
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Employee Group: Temporary
Compensation Information
Compensation is competitive and commensurate with experience.
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