3 Optimisation Techniques Jobs

Techtinium Technologies is currently focused on developing an intelligent system to optimize workflows, create production plans, and schedule manufacturing operations. The ultimate goal is to empower manufacturing leaders to make quicker and more informed decisions using an AI-powered conversational interface. This interface will allow users to interact through chat, seamlessly handle operational data, and extract valuable insights from both real-time and historical data. The company is seeking a proactive technical leader who possesses the skills to design, architect, and construct the conversational AI system from scratch. The individual will be responsible for the following key areas: System Architecture & Development: - Designing and implementing a chat-based interface that is integrated with manufacturing data sources. - Creating natural language understanding (NLU) models to interpret user queries and convert them into workflow actions, database operations, or insight generation tasks. Conversational AI & Orchestration: - Integration with LLMs (e.g., OpenAI, Anthropic) for natural conversations. - Developing a domain-specific ontology and prompt-engineering framework for manufacturing terminology. - Designing a command execution layer to translate chat intents into system actions. Data & Insights: - Collaborating with the data team to establish data models for manufacturing workflows. - Constructing insight generation modules to answer specific queries or perform tasks like rescheduling orders. - Ensuring data security and implementing role-based access control mechanisms. Collaboration & Leadership: - Working closely with Product Managers, Manufacturing SMEs, and Data Scientists to define system capabilities. - Leading technical decision-making processes, providing guidance to junior engineers, and upholding best practices. The ideal candidate should possess the following skills and qualifications: - Proficiency in programming languages such as Python, Node.js, or Java. - Experience with conversational AI frameworks like Rasa, LangChain, LlamaIndex, or custom LLM integrations. - Strong background in Database Design and Query Optimisation, especially with PostgreSQL, MongoDB, or manufacturing ERP databases. - Familiarity with Operations Research, Scheduling Algorithms, or Optimisation techniques. - Knowledge of cloud-native architectures, including AWS, Azure, or GCP. - Excellent communication abilities to collaborate effectively with technical and non-technical stakeholders. - Entrepreneurial mindset, self-driven, and comfortable working in dynamic, early-stage environments. About Techtinium: Techtinium Technologies is renowned for turning innovative concepts into reality using cutting-edge technology solutions. The company's commitment to building enduring partnerships with clients is evident in their delivery of customized software solutions that cater to specific business requirements. Specializing in AI, Data Science, Cloud Infrastructure, Mobile, and Web Development, Techtinium thrives on overcoming challenges and has successfully assisted more than 50 global customers in generating over $500M in revenue through innovative solutions.,

Are you passionate about harnessing the power of artificial intelligence to transform decision-making under uncertainty Do you aspire to develop innovative algorithms that can offer robust and reliable recommendations for critical real-world problems If your academic ambitions lie at the intersection of symbolic AI, optimization, and statistical reasoning, this PhD position at TU Delft could be your gateway to cutting-edge research and impactful career opportunities. Strong and confident decision-making is at the core of many societal and engineering challenges today. Yet, the complexity and uncertainty inherent in real-world systems often make it difficult to ascertain which variables truly influence outcomes. This PhD project invites you to leverage advanced combinatorial and algorithmic methods to identify these critical parameters, thus enabling more robust, data-efficient, and reliable decision-making processes. Delft University of Technology (TU Delft) is one of Europe's premier technical universities, renowned for its pioneering research, high-impact innovation, and vibrant academic community. Located in the historic city of Delft, the university boasts a strong tradition in engineering, science, and design, with a global reputation for excellence. TU Delft has been at the forefront of groundbreaking advancements, from the world-famous Dutch waterworks to state-of-the-art biotech and digital technologies. As a PhD candidate at TU Delft, you will join a diverse and international research environment, collaborating with leading experts and contributing to solutions for some of society's most pressing challenges. The focus of this PhD position is on Symbolic AI and Reasoning Under Uncertainty, with a particular emphasis on sensitivity analysis for decision-making models. In contemporary applications, algorithms generate recommendations based on complex models with numerous input parameters. However, determining which of these inputs genuinely drive the outcomes is crucial for resource allocation, contingency planning, and ensuring the robustness of decisions. Traditional sensitivity analysis often relies on computationally intensive simulations, which may overlook significant variables. This project proposes a paradigm shift: employing logic-based and structural methods to formally identify critical parameters. By exploiting the structure of logic problems, the research aims to deliver formal guarantees on robustness, reduce computational costs, and improve the reliability of decision-support systems. This approach holds immense promise for fields such as engineering, policy-making, and societal infrastructure, where robust and explainable AI is essential. As a PhD candidate, you will be part of the Algorithmics section within the Software Technology (ST) department at TU Delft, collaborating closely with the Statistics section of the Delft Institute of Applied Mathematics (DIAM). The project is supervised by a distinguished team: dr. ir. Sicco Verwer (promotor), dr. Fabian Mies, and dr. Anna Latour (co-promotores). Your research will build upon and expand knowledge in modeling and solving paradigms such as Boolean Satisfiability, Constraint Programming, and Mixed-Integer (Linear) Programming. You will also develop methods for reasoning about discrete probability distributions, sampling complex spaces, and statistical analysis. The role involves collaboration with other researchers and software engineers to create practical tools for both academic and societal stakeholders. You will disseminate your findings through publications and presentations at leading conferences and journals, providing excellent opportunities for international networking and professional growth. The Algorithmics section is a dynamic, diverse environment where PhD and postdoc researchers work together on theoretical and algorithmic contributions to intelligent decision-making. The group addresses challenges including scalability, model learning for planning and verification, and the integration of stakeholder preferences into algorithmic processes. TU Delft's interdisciplinary ecosystem further enhances your research experience, with opportunities to engage in cross-faculty initiatives addressing topics such as climate change, energy transition, and artificial intelligence. Applicants should possess a Master's degree in Computer Science, Operations Research, or a related field (required by the Graduate School of TU Delft), proficiency in the English language, demonstrable knowledge of reasoning paradigms such as Boolean Satisfiability, Constraint Programming, or Mixed Integer (Linear) Programming, programming skills in languages such as Java, Python, or C++, solid understanding of statistics and probability theory, excellent critical and analytical thinking skills, a proven record of and interest in further developing research skills, including self-organization, academic writing, and a critical attitude, strong enthusiasm for state-of-the-art algorithmic and optimization techniques, especially their application to decision-making, affinity for teaching and mentoring students, and ability to work effectively in a team and take initiative. This position is ideal for candidates who are passionate about symbolic AI, optimization, statistical reasoning, and who are eager to contribute to the advancement of robust decision-making methodologies. If you are driven to make a meaningful impact on decision-making methodologies and thrive in a collaborative, interdisciplinary environment, we encourage you to apply for this PhD position at TU Delft.,

As an experienced professional in the field, you will be expected to demonstrate proficiency in a range of key areas. Your expertise should include statistical modeling, traditional machine learning, and Gen AI. Moreover, you should possess knowledge of various deep learning models such as LSTM, N-BEATS, CNN, and RNN. In addition, you are required to be well-versed in optimization techniques including linear programming and mix integer programming, along with familiarity with optimization tools like Opensolver and Gurobi. Your role will involve working with Data Bricks and Snowflake, engaging with ML/DL models, and interacting directly with business stakeholders and customer FTEs. Therefore, strong technological skills and effective communication are essential for success in this position. The must-have skills for this role include Time Series Modelling (LSTN, CNN, N-BEATS, RNN), proficiency in Data Bricks, statistical knowledge, Python programming, optimization expertise, as well as experience with Opensolver and Gurobi. Additionally, it would be beneficial to have experience with GenAI and Snowflake. The ideal candidate should have a minimum of 8-10 years of experience in the field, showcasing a deep understanding of the mandatory skills required for this role. Your ability to leverage your expertise in time series modeling, data manipulation, statistical analysis, and optimization tools will be instrumental in driving successful outcomes for the organization.,