Core Banking Systems Engineer
Swisscom
Operate and improve Swisscom’s core banking and banking applications. Support integrations, incident resolution, releases, and technical projects.
Open
Gramian Consulting is a remote-first consulting firm focused on engineering, data, and AI talent. It helps organizations expand technical capacity through talent augmentation, recruiting, dedicated teams, and contractor management, while providing services such as LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure. The firm also supports individual career development through mentorship and education programs covering career readiness, interview preparation, and international market orientation. Its work combines hands-on engineering and recruiting experience to help clients build technical teams and apply AI to business needs.
Staff Research Engineer, AI and Machine Learning — India Remote
Lead frontier AI research at Gramian Consulting by designing experiments, prototypes, and evaluation systems. This contract role focuses on advancing machine learning methods and translating research into practical technical outcomes.
Description
- Study the capabilities, limitations, and training approaches of frontier AI systems.
- Define research questions that guide AI products, platforms, and technical direction.
- Investigate synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation methods.
- Track advances in machine learning and identify opportunities for substantive technical contributions.
- Build research-quality datasets, experiments, prototypes, tools, and evaluation frameworks.
- Train, test, and assess models with current AI and machine learning technologies.
- Interpret experimental results and draw conclusions supported by evidence.
- Implement disciplined practices for data quality, reproducibility, experimental design, and evaluation.
- Refine research hypotheses into validated technical insights through iteration.
- Partner with Research, Engineering, Product, and Operations teams to apply findings to real-world use cases.
- Present technical results clearly to specialist and cross-functional audiences.
- Support technical reports, publications, open-source work, workshops, or conferences when relevant.
- Mentor engineers and researchers while participating in technical reviews and discussions.
Requirements
- A Ph.D. or master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical discipline.
- At least 7 years of professional experience, including substantial research engineering work in machine learning or frontier AI systems.
- Strong machine learning fundamentals and practical experience designing experiments, training and evaluating models, or building AI systems.
- Research experience in synthetic or agentic data generation, reinforcement learning or post-training, model understanding, AI evaluation, benchmarks, or agent and tool-use systems.
- Advanced Python skills for rapidly implementing, testing, and refining research ideas.
- Hands-on familiarity with contemporary AI and machine learning frameworks, tools, and research workflows.
- Sound scientific judgment regarding experimental rigor, data quality, reproducibility, and evidence-based decisions.
- Excellent technical communication skills and the ability to work independently across research and engineering teams.
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