Join us at Rhesis AI – Ensuring Gen AI applications deliver value, not surprises!
At Rhesis AI, we empower organizations to develop and deploy Gen AI applications that meet high standards for reliability, robustness, and compliance. Our testing platform helps AI teams to validate and secure Gen AI applications across diverse use cases and industries, ensuring they perform predictably, adhere to restrictions, and meet client expectations.
If you’re passionate about advancing trustworthy AI that responsibly serves humanity, we invite you to join our mission.
Tasks

Important Skills

• Hands-on experience with Large Language Models and Generative AI
• Strong background in Python programming, ML frameworks (JAX, PyTorch, TensorFlow, HuggingFace Transformers, Scikit-Learn), and MLOps expertise.
• Knowledge of ML fundamentals and software engineering best practices, such as testing.
• Experience in the development of robust, production-ready code.
• Proficiency in CI/CD, DevOps pipelines, and containerization.
• Experience in Natural Language Processing

Awesome Skills

• Experience with research, development and/or replication of state-of-the-art ML models / papers
• Experience with infrastructure automation (e.g., Infrastructure as Code).
• Building near-real-time and real-time data pipelines (e.g. Kafka)
• Working with data intensive pipelines (e.g. using Spark and/or Databricks)
• Knowledge of cloud-native solutions (GCP, Azure, AWS)
• Building and fine-tuning deep learning models for deployment and inferenc

Overall skills

• Solid software engineering skills with the ability to design sophisticated software systems, curate datasets, and train models for scientific applications.
• Proficiency in Python programming and developing production-ready code for data-driven applications.
• Expertise in system design and problem-solving, including the ability to decompose complex problems into simpler solutions.
• Familiarity with modern development practices and tools such as version control, CI/CD, containerization, and cloud-native solutions (e.g., Azure or AWS).
• Experience in building real-time data pipelines, natural language processing, container-based development, and infrastructure automation.
• Previous roles as a Senior Machine Learning Engineer with MLOps experience, optimizing and deploying deep learning models

WHAT YOU WILL DO:

• Oversee and/or execute the design, development, fine-tuning, and deployment of large language models and generative AI systems for the Rhesis AI platform.
• Implement LLMOps best practices to streamline the machine learning lifecycle from data ingestion to model deployment and continuous improvement.
• Drive research and development to replicate state-of-the-art ML models and papers, as well as carry out independent research efforts (yes, you can publish!).
• Develop LLM-enabled data pipelines using tools job orchestration tools to integrate large-scale language models into data workflows.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and processes.
• Stay updated on the latest advancements in AI, ML, and NLP to inform strategic decision-making and product innovation.
• Lead research efforts to ensure compliance with regulatory requirements and ethical standards in AI development and deployment.
• While your role will be primarily focused on artificial intelligence and machine learning, you will occasionally contribute to data engineering, MLOps, and general software engineering tasks as needed by the team.
• As part of a small and dynamic team, you will be expected to pitch in where necessary and collaborate across disciplines to help build and enhance the product.
  Requirements

YOU ARE GREAT FOR THIS ROLE, IF YOU HAVE:

Important Skills

• Hands-on experience with Large Language Models and Generative AI
• Strong background in Python programming, ML frameworks (JAX, PyTorch, TensorFlow, HuggingFace Transformers, Scikit-Learn), and MLOps expertise.
• Knowledge of ML fundamentals and software engineering best practices, such as testing.
• Experience in the development of robust, production-ready code.
• Proficiency in CI/CD, DevOps pipelines, and containerization.
• Experience in Natural Language Processing.

Awesome Skills

• Experience with research, development and/or replication of state-of-the-art ML models / papers
• Experience with infrastructure automation (e.g., Infrastructure as Code).
• Building near-real-time and real-time data pipelines (e.g. Kafka)
• Working with data intensive pipelines (e.g. using Spark and/or Databricks)
• Knowledge of cloud-native solutions (GCP, Azure, AWS)
• Building and fine-tuning deep learning models for deployment and inference

Overall skills

• Solid software engineering skills with the ability to design sophisticated software systems, curate datasets, and train models for scientific applications.
• Proficiency in Python programming and developing production-ready code for data-driven applications.
• Expertise in system design and problem-solving, including the ability to decompose complex problems into simpler solutions.
• Familiarity with modern development practices and tools such as version control, CI/CD, containerization, and cloud-native solutions (e.g., Azure or AWS).
• Experience in building real-time data pipelines, natural language processing, container-based development, and infrastructure automation.
• Previous roles as a Senior Machine Learning Engineer with MLOps experience, optimizing and deploying deep learning models.

In summary, the candidate should have a strong background in both machine learning and software engineering, with specific expertise in developing and deploying advanced machine learning models, along with a solid understanding of modern development practices and tools.
Benefits
We’re excited to offer a fixed one-year contract (initially, with likely extension), starting 1 February, along with a range of benefits to support our team members, including:
1. Comprehensive compensation package including shares: We offer salaries and benefits tailored to your experience and qualifications, along with the opportunity to gain ownership in the company.
2. Professional development opportunities: We provide resources and support for ongoing learning and career growth, including access to training programs, workshops, and conferences.
3. Flexible work arrangements: We understand the importance of work-life balance and offer flexible working options to accommodate personal needs and preferences.
4. A supportive and collaborative work environment: We foster a culture of teamwork, collaboration, and mutual respect, where every team member is valued and supported in their professional and personal growth.
We welcome applicants from all backgrounds, irrespective of gender, nationality, religion, or any other personal characteristic. Our organization values diversity and inclusion, and we encourage individuals from all walks of life to apply for this position. Even if you believe you may not meet all the listed requirements, we encourage you to submit your application. We believe that diverse perspectives enrich our team and contribute to our collective success. Your unique skills, experiences, and perspectives are highly valued, and we look forward to considering your application