5 Reproducibility Jobs

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. We are looking to hire individuals with strong AI Enabled Automation skills who are interested in applying AI in the process automation space using technologies such as Azure, AI, ML, Deep Learning, NLP, GenAI, large Lang Models (LLM), RAG, Vector DB, Graph DB, and Python. Responsibilities: - Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. - Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals to demonstrate the potential of AI enabled automation applications. - Ensure seamless integration of optimized solutions into the overall product or system. - Collaborate with cross-functional teams to understand requirements, integrate solutions into cloud environments (Azure, GCP, AWS, etc.), and ensure alignment with business goals and user needs. - Educate the team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project. Technical Skills Requirements: - 9 to 13 years of relevant professional experience. - Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. - Strong foundation in ML algorithms, feature engineering, and model evaluation (Must). - Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP (Must). - Experience in GenAI technologies such as LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. - Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI (Agentic Framework). - Knowledge of retrieval augmented generation (RAG) and Knowledge Graph RAG. - Experience with multi-agent orchestration, memory, and tool integrations. - Experience/implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility) Good to have. - Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. - Good understanding of data pipelines, APIs, and distributed systems. - Build observability into AI systems latency, drift, performance metrics. - Strong written and verbal communication, presentation, client service, and technical writing skills in English for both technical and business audiences. - Strong analytical, problem-solving, and critical thinking skills. - Ability to work under tight timelines for multiple project deliveries. What we offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. While we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY, you can be who you are and express your point of view, energy, and enthusiasm, wherever you are in the world. It's how you make a difference. EY | Building a better working world: EY exists to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

As a Senior R Developer at MResult, you will play a crucial role in supporting the development, validation, and deployment of models and tools used in drug development and clinical research. Your responsibilities will include developing and maintaining R scripts, packages, and Shiny applications for data analysis and visualization. You will be involved in performing statistical analysis and data manipulation related to clinical trials and PK/PD data. Collaboration with pharmacometricians and clinical scientists will be key as you work together to develop PK models and support modeling workflows. Automating data cleaning, processing, and reporting tasks will be part of your daily activities. You will also integrate PK/PD datasets with clinical trial data and prepare analysis-ready datasets. Ensuring code validation and documentation as per regulatory compliance standards such as FDA and EMA will be essential. In addition to technical responsibilities, you will generate reports and graphical outputs using tools like R Markdown and participate in cross-functional project teams, providing input on statistical and modeling strategies. To succeed in this role, you should have a Bachelor's or Masters degree in Statistics, Data Science, Bioinformatics, Pharmacology, or a related field and a minimum of 5 years of experience in R programming. Experience with R package development, version control using Git/GitHub, and hands-on experience in Pharmacokinetics (PK) is required, preferably in a clinical or pharmaceutical setting. A strong understanding of PK/PD concepts, NONMEM outputs, and model diagnostics will be beneficial. Excellent problem-solving skills, the ability to communicate complex results to non-technical stakeholders, attention to detail, and a commitment to code quality and reproducibility are essential qualities for success in this role. At MResult, you will have the opportunity to work with some of the world's most recognized brands, access growth opportunities, and contribute to cutting-edge solutions while enjoying the flexibility of hybrid work models. As an equal-opportunity employer, MResult is committed to fostering an inclusive environment free of discrimination and harassment. Join us at MResult, where your ideas help shape the future.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

About the Team and Our Scope We are a forward-thinking tech organization within Swiss Re, delivering transformative AI/ML solutions that redefine how businesses operate. Our mission is to build intelligent, secure, and scalable systems that deliver real-time insights, automation, and high-impact user experiences to clients globally. You'll join a high-velocity AI/ML team working closely with product managers, architects, and engineers to create next-gen enterprise-grade solutions. Our team is built on a startup mindset - bias to action, fast iterations, and ruthless focus on value delivery. We're not only shaping the future of AI in business - we're shaping the future of talent. This role is ideal for someone passionate about advanced AI engineering today and curious about evolving into a product leadership role tomorrow. You'll get exposure to customer discovery, roadmap planning, and strategic decision-making alongside your technical contributions. Role Overview As an AI/ML Engineer, you will play a pivotal role in the research, development, and deployment of next-generation GenAI and machine learning solutions . Your scope will go beyond retrieval-augmented generation (RAG) to include areas such as prompt engineering, long-context LLM orchestration, multi-modal model integration (voice, text, image, PDF), and agent-based workflows. You will help assess trade-offs between RAG and context-native strategies, explore hybrid techniques, and build intelligent pipelines that blend structured and unstructured data. You'll work with technologies such as LLMs, vector databases, orchestration frameworks, prompt chaining libraries, and embedding models, embedding intelligence into complex, business-critical systems. This role sits at the intersection of rapid GenAI prototyping and rigorous enterprise deployment, giving you hands-on influence over both the technical stack and the emerging product direction. Key Responsibilities Build Next-Gen GenAI Pipelines : Design, implement, and optimize pipelines across RAG, prompt engineering, long-context input handling, and multi-modal processing. Prototype, Validate, Deploy : Rapidly test ideas through PoCs, validate performance against real-world business use cases, and industrialize successful patterns. Ingest, Enrich, Embed: Construct ingestion workflows including OCR, chunking, embeddings, and indexing into vector databases to unlock unstructured data. Integrate Seamlessly: Embed GenAI services into critical business workflows, balancing scalability, compliance, latency, and observability. Explore Hybrid Strategies: Combine RAG with context-native models, retrieval mechanisms, and agentic reasoning to build robust hybrid architectures. Drive Impact with Product Thinking : Collaborate with product managers and UX designers to shape user-centric solutions and understand business context. Ensure Enterprise-Grade Quality: Deliver solutions that are secure, compliant (e.g., GDPR), explainable, and resilient - especially in regulated environments. What Makes You a Fit Must-Have Technical Expertise Proven experience with GenAI techniques and LLMs , including RAG, long-context inference, prompt tuning, and multi-modal integration. Strong hands-on skills with Python , embedding models, and orchestration libraries (e.g., LangChain, Semantic Kernel, or equivalents). Comfort with MLOps practices , including version control, CI/CD pipelines, model monitoring, and reproducibility. Ability to operate independently, deliver iteratively, and challenge assumptions with data-driven insight. Understanding of vector search optimization and retrieval tuning. Exposure to multi-modal models Nice-To-Have Qualifications Experience building and operating AI systems in regulated industries (e.g., insurance, finance, healthcare). Familiarity with Azure AI ecosystem (e.g., Azure OpenAI, Azure AI Document Intelligence, Azure Cognitive Search) and deployment practices in cloud-native environments. Experience with agentic AI architectures , tools like AutoGen, or prompt chaining frameworks. Familiarity with data privacy and auditability principles in enterprise AI. Bonus: You Think Like a Product Manager While this role is technical at its core, we highly value candidates who are curious about how AI features become products . If you're excited by the idea of influencing roadmaps, shaping requirements, or owning end-to-end value delivery - we'll give you space to grow into it. This is a role where engineering and product are not silos . If you're keen to move in that direction, we'll mentor and support your evolution. Why Join Us You'll be part of a team that's pushing AI/ML into uncharted, high-value territory. We operate with urgency, autonomy, and deep collaboration. You'll prototype fast, deliver often, and see your work shape real-world outcomes - whether in underwriting, claims, or data orchestration. And if you're looking to transition from deep tech to product leadership , this role is a launchpad. Swiss Re is an equal opportunity employer . We celebrate diversity and are committed to creating an inclusive environment for all employees. Keywords: Reference Code: 134317

Plan and execute advanced microbiological research to develop new products and optimize existing processes. Conduct microbial culturing, isolation, identification, and characterization using classical and molecular biology techniques.