68 Ontologies Jobs nearby Palakkad

As an AI Architect at Mobius, you will be responsible for designing architectures for meta-learning, self-reflective agents, and recursive optimization loops. Your role will involve building simulation frameworks grounded in Bayesian dynamics, attractor theory, and teleo-dynamics. Additionally, you will develop systems that integrate graph rewriting, knowledge representation, and neurosymbolic reasoning. Your tasks will also include conducting research on fractal intelligence structures, swarm-based agent coordination, and autopoietic systems. Furthermore, you will contribute to advancing Mobius's knowledge graph with ontologies supporting logic, agency, and emergent semantics. You will integrate logic into distributed, policy-scoped decision graphs aligned with business and ethical constraints. It will also be expected of you to publish cutting-edge results and mentor contributors in reflective system design and emergent AI theory. Lastly, you will build scalable simulations of multi-agent, goal-directed, and adaptive ecosystems within the Mobius runtime. **Key Responsibilities:** - Design architectures for meta-learning, self-reflective agents, and recursive optimization loops. - Build simulation frameworks grounded in Bayesian dynamics, attractor theory, and teleo-dynamics. - Develop systems integrating graph rewriting, knowledge representation, and neurosymbolic reasoning. - Conduct research on fractal intelligence structures, swarm-based agent coordination, and autopoietic systems. - Advance Mobius's knowledge graph with ontologies supporting logic, agency, and emergent semantics. - Integrate logic into distributed, policy-scoped decision graphs aligned with business and ethical constraints. - Publish cutting-edge results and mentor contributors in reflective system design and emergent AI theory. - Build scalable simulations of multi-agent, goal-directed, and adaptive ecosystems within the Mobius runtime. **Qualification Required:** - Proven expertise in meta-learning, recursive architectures, and AI safety. - Experience in distributed systems, multi-agent environments, and decentralized coordination. - Strong implementation skills in Python (required), with additional proficiency in C++, functional or symbolic languages being a plus. - Publication record in areas intersecting AI research, complexity science, and/or emergent systems.,

As a highly skilled and experienced Hands-on Palantir Architect, your role will involve the end-to-end design, development, and implementation of complex data solutions on the Palantir platform. You will need to be proficient in both architectural design and hands-on development, including building robust data pipelines and creating powerful applications for critical insights. Key Responsibilities: - Lead the technical design and architecture of solutions on the Palantir platform, ensuring scalability, performance, and security. - Actively participate in the development of data pipelines using PySpark, Spark SQL, TypeScript, and Python to transform and integrate data from various sources. - Construct and configure interactive applications and dashboards using Palantir's tools such as Workshop, Quiver, and Slate. - Serve as a technical expert and mentor for junior team members, fostering best practices and knowledge sharing within the team. - Work closely with business stakeholders, data scientists, and engineers to translate business requirements into technical solutions. - Identify and address performance bottlenecks to ensure the efficiency and reliability of data pipelines and applications. Qualifications Required: - 4+ years of experience as a Palantir Architect or Palantir Solution Developer. - Deep, hands-on experience with Palantir Foundry or Palantir Gotham, including data integration, ontology modeling, and application development. - Strong proficiency in TypeScript, Python, and PySpark is essential. Experience with Scala and SQL is a plus. - Solid understanding of data warehousing, ETL/ELT processes, and data modeling concepts. - Excellent verbal and written communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.,

Your role: You will be part of a team at UBS responsible for building firmwide Data Observability Components on Azure. Your responsibilities will include designing, developing, testing, and supporting Data Observability components/platforms/environments. Additionally, you will collaborate with other teams and divisions to ensure delivery deadlines are met, comply with applicable policies and processes, and contribute to agile ceremonies. Responsibilities include: - Designing/documenting, developing, reviewing, testing, releasing, and supporting Data Observability components/platforms/environments - Contributing to agile ceremonies e.g. daily stand-ups, backlog refinement, iteration planning, iteration reviews, retrospectives - Complying with the firm's applicable policies and processes - Collaborating with other teams and divisions using Data Observability services, related guilds, and other Data Mesh Services teams - Ensuring delivery deadlines are met Your team: You will work alongside data scientists, data engineers, full-stack developers, DevSecOps engineers, and knowledge engineers within Group CTO. The team operates globally with a focus on providing Data Observability services to automate and scale data management. You will have opportunities to learn and work with technologies such as Azure Cloud, AI (ML and GenAI models), web user interface (React), data storage (Postgres, Azure), REST APIs, Kafka, Great Expectations, and ontology models. Your expertise: - Ideally 4 years of experience or similar transferrable skills in data transformations, Spark, python, database design and development in any database - CI/CD pipelines, security risk mitigation, infrastructure as code (e.g. Terraform), monitoring, Azure development - Agile software practices and tools, performance testing, unit and integration testing - Identifying root-causes and designing and implementing the solution - Collaborating with other teams to achieve common goals - Learning and reskilling in new technologies About Us: UBS is the world's largest and the only truly global wealth manager, operating through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management, and the Investment Bank. With a presence in over 50 countries, we differentiate ourselves through our global reach and expertise. Join us: UBS offers flexible working arrangements and a purpose-led culture that fosters collaboration and innovation. We encourage individuals with diverse backgrounds and experiences to join #teamUBS and contribute to our ongoing success.,

As a Senior Lead Data Architect at JPMorgan Chase within Corporate Technology, you play a crucial role in developing high-quality data architecture solutions for various software applications and platform products. Your expertise in multiple data architecture domains contributes significantly to business impact and the shaping of global target state architecture. **Key Responsibilities:** - Represent the data architecture team at technical governance bodies and provide feedback on proposed improvements - Evaluate new and current technologies using existing data architecture standards and frameworks - Provide technical guidance and direction to support the business and its technical teams, contractors, and vendors - Develop secure, high-quality production code and review and debug code written by others - Drive data architecture decisions impacting product design, application functionality, and technical operations - Serve as a subject matter expert in one or more areas of focus - Contribute to the engineering community by advocating firmwide data frameworks, tools, and practices - Influence peers and project decision-makers to consider leading-edge technologies - Advise junior architects and technologists - Promote a team culture of diversity, opportunity, inclusion, and respect **Qualifications Required:** - Formal training or certification in Information Engineering concepts with 5+ years of applied experience - Hands-on experience in system design, application development, testing, and operational stability - Advanced proficiency in data modeling, data governance, and data architecture within a finance organization - Demonstrated experience with Data Mesh and Databricks - Advanced proficiency in one or more programming languages, applications, and architecture - In-depth knowledge of architecture, applications, and technical processes in at least one technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile) - Ability to independently solve design and functionality problems with minimal oversight - Practical experience with cloud-native technologies - Ability to evaluate current and emerging technologies to recommend solutions for future state architecture - Commitment to fostering a culture of diversity, opportunity, inclusion, and respect The job also requires past experience in Corporate Functions within a financial company, experience creating or implementing organizational-level data standards, and experience defining taxonomy and ontology.,

As a Principal Data Engineer at GSK, you will play a crucial role in transforming the commercial manufacturing and supply chain organization to increase capacity and speed for transferring new products from the R&D organization. Data and AI are vital components in achieving this goal, ultimately leading to quicker medicine launches and a positive impact on patients. **Key Responsibilities:** - Lead the technical design, development, testing, and release of the CMC Knowledge Graph and other Data & AI solutions in the CMC/NPI portfolio. - Provide Data Engineering leadership, technical guidance, and mentorship to the development team, driving performance and continuous improvement. - Address technical challenges throughout the product life-cycle with hands-on technical problem-solving expertise. - Collaborate with Product Management to create and evolve a compelling product vision and roadmap, engaging users and stakeholders to gather feedback. - Ensure compliance with relevant policies and procedures, contributing to and evolving architecture standards. - Stay updated with the latest advancements in Knowledge Graph and related technologies, recommending and implementing improvements to enhance system functionality. **Qualifications Required:** - Proven track record in delivering complex data engineering projects in a cloud environment, preferably Azure, with at least 16+ years of experience. - Strong technical expertise in designing, developing, and supporting Knowledge Graphs, including proficiency in graph technologies such as RDF, OWL, SPARQL, and Cypher. - Experience in leading and managing technical teams, data modeling/ontologies, data integration, and data transformation techniques. - Strong programming skills, proficiency in code repositories like Git, and experience with DevOps principles and CI/CD practices. - Understanding of pharmaceutical industry data and domain knowledge within CMC would be a plus. - Knowledge of GxP compliance requirements and experience implementing them in data engineering projects. Join GSK in its mission to unite science, technology, and talent to get ahead of disease together and positively impact the health of billions of people. GSK is committed to creating a workplace where individuals can thrive, grow, and contribute to meaningful advancements in healthcare. If you share our ambition, this is an exciting opportunity to be part of our journey to get Ahead Together.,

As an AI Architect in this role, you will be responsible for designing and delivering scalable AI/ML solutions in production environments. You should have hands-on experience with Graph Databases like Neo4j, AWS Neptune, or MemGraph. Your primary focus will be proposing end-to-end architecture and solutions that meet complex business needs. Key Responsibilities: - Design and architect AI/ML systems using Graph Databases (Neo4j, AWS Neptune, or MemGraph) in production environments. - Analyze current systems and propose scalable solutions aligned with business objectives. - Evaluate different graph technologies and recommend the most suitable for specific use cases. - Develop Proof of Concepts (PoCs), technical prototypes, and production-grade AI pipelines integrating graph technologies. - Collaborate with data scientists, ML engineers, and backend developers for the seamless integration of AI models. - Define data modeling strategies for graph databases, including ontology/taxonomy design. - Establish best practices, documentation, and governance models for graph-based AI systems. Qualifications Required: - 10+ years of experience in AI/ML solution architecture or enterprise-level software development. - Strong hands-on experience with at least one graph database: Neo4j, AWS Neptune, or MemGraph. - Proven ability to design AI/ML solutions integrated with graph data modeling. - Deep understanding of data structures, algorithms, and distributed systems. - Hands-on experience with Python, Java, or Scala in AI/ML contexts. - Ability to facilitate technical discussions and make independent architectural decisions.,

As a Data Analyst in the Content Operations Team at our company, you will play a crucial role in shaping the quality and structure of content on our customer-facing platforms. Your responsibilities will include: - Evaluating and analyzing external content sources for relevance, quality, structure, and usability - Performing data quality assessments and assisting in designing data profiling frameworks - Collaborating with product managers, data engineers, and content specialists to onboard new content sources - Creating reports, dashboards, and documentation to share findings and support decisions - Improving existing content through structured analysis and feedback loops - Translating technical findings into business-friendly presentations for non-technical stakeholders - Supporting automation efforts for content transformation and integration - Participating in the continuous improvement of content ingestion processes and validation workflows - Ensuring compliance with data usage policies and content governance standards Qualifications required for this role include: - Minimum 4 years of experience as a Data Analyst or in a similar data-focused role - Bachelor's degree in Information Technology, Computer Science, Data Analytics, or a related field - Experience with AWS services (e.g., S3, Athena) - Strong Excel and SQL skills, preferably PostgreSQL - Familiarity with data quality metrics and frameworks - Metadata analysis and taxonomy/ontology understanding - Experience with data modeling and structured/unstructured data - Strong data wrangling and exploration experience It would be beneficial if you also had experience with: - Databricks or similar data platforms - Data visualization tools such as Power BI - Exposure to API integration and working with JSON/XML data As a member of the Content Operations Team, you will be part of a collaborative, innovative, and accountable environment where your contributions have a real impact on products used by thousands of customers. Our team values collaboration, innovation, and accountability in delivering structured, high-quality content to our global customers.,

Role Overview: You will play a key role in developing clinical database products in various therapeutic areas such as Metabolic & CV, Neuroscience, Autoimmune, Oncology, Respiratory, etc. Your primary focus will be to ensure the high quality of these products to support Meta-analysis. Additionally, you will be responsible for analyzing and annotating trial design information, treatments, demographics, and outcomes data from clinical literature. Your role will also involve digitizing results from graphs and working closely with the team to understand and contribute to database rules and quality processes. Key Responsibilities: - Develop clinical database products with high quality to support Meta-analysis - Analyze and annotate trial design information, treatments, demographics, and outcomes data from clinical literature - Digitize results from graphs for outcomes reported on linear, logarithmic, and semi-log scales - Collaborate with the lead consultant, peer data analyst, and Quality manager to contribute to database rules and quality processes - Undergo relevant training programs to enhance skills in Statistics, R coding, Systematic literature review, and Data analysis methods Qualifications: - Master's in Pharmacology or Pharmaceutics (with relevant experience), PharmaD, Clinical Practice, Master's in Public Health, or Epidemiology - Minimum 1-2 years of experience in Information science, Systematic Literature review, Health-economics, and public health sectors, pharmaceutical industry experience preferred - Strong knowledge of Pharmacology and clinical research - Knowledge of clinical development, post-approval phases, trial designs, Pharma Industry data standards/ontologies - Knowledge of statistics, data management tools like R is an added advantage Additional Company Details: Certara is a leading Clinical Pharmacology & Pharmacometric organization globally, offering various career pathways to match the ambition and personal interests of its employees. The company integrates advanced simulation approaches into critical drug development deliverables to inform decision-making and strengthen global regulatory submissions. With a successful track record and extensive expertise in working on numerous drug development projects, Certara brings value to each assignment.,