65 Julia Jobs

We are seeking a highly analytical Quantitative Research Analyst to join our AIF Quant Fund team. The ideal candidate brings strong buy-side experience in systematic investment strategies and will play a key role in developing, implementing, and maintaining sophisticated quantitative models that drive our alternative investment approach. About The Role The Quantitative Research Analyst will be responsible for various key responsibilities that include model development, data infrastructure management, strategy testing, risk management, and technology : Model Development & Research Design and build multi-factor models for equity, fixed income, and alternative asset classes. Develop alpha generation signals and systematic trading strategies across multiple time horizons. Research and implement new quantitative factors using academic literature and market insights. Enhance existing models through continuous performance monitoring and iterative improvements. Data Infrastructure & Analytics Manage large-scale financial datasets using Snowflake, SQL, and cloud-based platforms. Build automated data pipelines for real-time and historical market data processing. Ensure data quality, integrity, and optimize query performance for research workflows. Develop efficient storage solutions for multi-asset research environments. Strategy Testing & Validation Conduct comprehensive back testing across multiple market cycles using robust statistical methods. Perform out-of-sample testing, walk-forward analysis, and Monte Carlo simulations. Generate detailed performance attribution and risk decomposition analysis. Document model assumptions, limitations, and validation results. Risk Management & Monitoring Build risk management frameworks including VaR, stress testing, and scenario analysis. Monitor portfolio exposures, concentration risks, and factor loadings in real-time. Develop automated alerting systems for model degradation and performance anomalies. Support portfolio optimization and construction processes. Technology & Automation Develop Python-based research and production systems with focus on scalability. Create automated model monitoring, reporting, and alert generation frameworks. Collaborate on technology infrastructure decisions and platform evaluations. Maintain code quality and documentation standards. Qualifications Professional Experience : 48 years of buy-side quantitative research in asset management, hedge funds, or proprietary trading. Proven track record in systematic investment strategy development and implementation. Experience with institutional-grade quantitative research and portfolio management. Technical Proficiency Programming : Advanced Python (pandas, numpy, scipy, scikit-learn, quantitative libraries). Database : Hands-on Snowflake and SQL experience with large-scale data environments. Analytics : Statistical modeling, econometrics, and machine learning techniques. Platforms : Bloomberg Terminal, Refinitiv, or equivalent financial data systems. Quantitative Expertise Deep understanding of factor models, portfolio optimization, and systematic risk management. Knowledge of derivatives pricing, fixed income analytics, and alternative investment structures. Experience with market microstructure analysis and high-frequency data processing. Familiarity with performance attribution methodologies and benchmark & Analysis : Strong problem-solving abilities with exceptional attention to detail. Ability to translate quantitative insights into actionable investment recommendations. Excellent presentation skills for communicating complex research to stakeholders. Collaborative approach to working in cross-functional investment teams. Educational Background Master's degree in Finance, Economics, Mathematics, Statistics, Physics, or Engineering. CQF, CFA, FRM or equivalent professional certification preferred. Strong academic foundation with demonstrated quantitative aptitude. Regulatory Awareness Understanding of SEBI AIF regulations and compliance frameworks. Knowledge of investment management risk controls and regulatory reporting requirements. Preferred Skills Industry Recognition : Published quantitative research or contributions to investment thought leadership. Multi-Asset Expertise : Experience across equity, fixed income, commodities, and alternative investments. Innovation Mindset : Interest in machine learning, alternative data, and emerging quantitative techniques. Advanced Programming : Proficiency in additional languages such as R, C++, or Julia; experience with version control (Git) and code optimization techniques. Domain Specialization : Strong background in specific asset classes such as Indian equities & emerging markets. Entrepreneurial Drive : Self-motivated individual comfortable building scalable systems from ground-up in a growing AIF technology environment. Industry Certifications : Additional qualifications or specialized quantitative finance credentials will be a plus. Alternative Data & AI : Experience with NLP and AI techniques for extracting investment signals from alternative text data sources (such as Filings, Analyst Reports and Transcripts) and developing reasoning-based AI models for systematic decision-making will be a plus. Pay range and compensation package : Competitive with industry standards, including performance-based incentives. (ref:hirist.tech)

The candidate should have experience in AI Development including experience in developing, deploying, and optimizing AI and Generative AI solutions. The ideal candidate will have a strong technical background, hands-on experience with modern AI tools and platforms, and a proven ability to build innovative applications that leverage advanced AI techniques. You will work collaboratively with cross-functional teams to deliver AI-driven products and services that meet business needs and delight end-users. Key Prerequisites  Experience in AI and Generative AI Development  Experience in Design, develop, and deploy AI models for various use cases, such as predictive analytics, recommendation systems, and natural language processing (NLP).  Experience in Building and fine-tuning Generative AI models for applications like chatbots, text summarization, content generation, and image synthesis.  Experience in implementation and optimization of large language models (LLMs) and transformer-based architectures (e.g., GPT, BERT).  Experience in ingestion and cleaning of data  Feature Engineering and Data Engineering  Experience in Design and implementation of data pipelines for ingesting, processing, and storing large datasets.  Experience in Model Training and Optimization  Exposure to deep learning models and fine-tuning pre-trained models using frameworks like TensorFlow, PyTorch, or Hugging Face.  Exposure to optimization of models for performance, scalability, and cost efficiency on cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI).  Hands-on experience in monitoring and improving model performance through retraining and evaluation metrics like accuracy, precision, and recall. AI Tools and Platform Expertise  OpenAI, Hugging Face  MLOps tools  Generative AI-specific tools and libraries for innovative applications. Technical Skills 1. Strong programming skills in Python (preferred) or other languages like Java, R, or Julia. 2. Expertise in AI frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face. 3. Proficiency in working with transformer-based models (e.g., GPT, BERT, T5, DALL-E). 4. Experience with cloud platforms (AWS, Azure, Google Cloud) and containerization tools (Docker, Kubernetes). 5. Solid understanding of databases (SQL, NoSQL) and big data processing tools (Spark, Hadoop).

2 Years of experience mandatory Machine Learning (ML): Supervised & unsupervised learning Regression, classification, clustering Model evaluation and tuning Deep Learning: Neural networks (CNNs, RNNs, LSTMs, Transformers) Frameworks: TensorFlow, PyTorch, Keras Data Science & Analytics: Data cleaning and pre-processing Feature engineering EDA (Exploratory Data Analysis) Programming: Proficient in Python (NumPy, pandas, scikit-learn, matplotlib, etc.) Optional: R, Julia, or C++ NLP & LLMs: Text preprocessing, embeddings (word2vec, BERT, etc.) Fine-tuning and using LLMs (e.g., GPT, BERT, T5) Computer Vision: Image classification, object detection OpenCV, YOLO, or similar libraries Math & Stats: Linear algebra, probability, calculus Statistical modeling Infrastructure & DevOps Cloud platforms: AWS, GCP, Azure MLOps: ML pipelines, model versioning (e.g., MLflow, DVC) Docker, Kubernetes for deployment Git and version control Understanding business problems and translating them into AI solutions Job Type: Full-time Pay: ₹50,499.45 - ₹75,027.94 per month Schedule: Day shift Experience: AL/ML: 2 years (Required) Work Location: In person

Othor AI is seeking a talented and motivated Mathematician Research Intern to join our decision intelligence team. This internship offers an exceptional opportunity to work at the intersection of advanced mathematics, artificial intelligence, and real-world decision-making systems. You&aposll contribute to cutting-edge research that transforms how organizations make complex decisions through mathematical modeling and AI-driven insights. Key Responsibilities Develop and analyze mathematical models for decision optimization problems Research and implement novel algorithms for multi-criteria decision analysis Collaborate with AI researchers to integrate mathematical frameworks into machine learning pipelines Conduct theoretical analysis of decision intelligence algorithms and their convergence properties Prototype mathematical solutions using Python, R, or MATLAB Contribute to research publications and technical documentation Present findings to cross-functional teams and external stakeholders Assist in developing mathematical foundations for explainable AI decision systems Required Qualifications Currently pursuing or recently completed Master&aposs or PhD in Mathematics, Applied Mathematics, Operations Research, or related field Strong background in optimization theory, linear algebra, and probability theory Experience with mathematical modeling and algorithm development Proficiency in at least one programming language (Python, R, MATLAB, or Julia preferred) Knowledge of statistical analysis and numerical methods Excellent analytical and problem-solving skills Strong written and verbal communication abilities Ability to work independently and collaboratively in a fast-paced research environment Preferred Qualifications Experience with machine learning and artificial intelligence concepts Background in game theory, decision theory, or multi-objective optimization Familiarity with deep learning frameworks (TensorFlow, PyTorch) Experience with mathematical software (Mathematica, Maple, or similar) Previous research experience in applied mathematics or related fields Publications in peer-reviewed journals or conferences Knowledge of reinforcement learning or Bayesian methods What We Offer Mentorship from leading researchers in decision intelligence and AI Opportunity to work on challenging, real-world mathematical problems Access to cutting-edge computational resources and research tools Collaborative environment with opportunities for professional growth Competitive internship compensation Potential for publication opportunities and conference presentations Flexible hybrid work arrangements Networking opportunities within the AI and decision science community Duration & Commitment 3-6 month internship with potential for extension Full-time commitment (40 hours/week) preferred Part-time arrangements considered for exceptional candidates Start date flexible based on candidate availability About Othor AI Othor AI is at the forefront of decision intelligence, developing AI systems that help organizations make better decisions through advanced mathematical modeling and machine learning. Our multidisciplinary team combines expertise in mathematics, computer science, and domain-specific knowledge to solve complex real-world problems. Show more Show less

Minimum 12+ years of relevant experience in building software applications in data and analytics field Enhance the go-to-market strategy by designing new and relevant solution frameworks to accelerate our clients journeys for impacting patient outcomes. Pitch for these opportunities and craft winning proposals to grow the Data Science Practice. Build and lead a team of data scientists and analysts, fostering a collaborative and innovative environment. Oversee the design and delivery of the models, ensuring projects are completed on time and meet business objectives. Engaging in consultative selling with clients to grow/deliver business. Develop and operationalize scalable processes to deliver on large & complex client engagements. Extensive hands-on experience with Python, R, or Julia, focusing on data science and generative AI frameworks. Expertise in working with generative models such as GPT, DALL-E, Stable Diffusion, Codex, and MidJourney for various applications. Proficiency in fine-tuning and deploying generative models using libraries like Hugging Face Transformers, Diffusers, or PyTorch Lightning. Strong understanding of generative techniques, including GANs, VAEs, diffusion models, and autoregressive models. Experience in prompt engineering, zero-shot, and few-shot learning for optimizing generative AI outputs across different use cases. Expertise in managing generative AI data pipelines, including preprocessing large-scale multimodal datasets for text, image, or code generation. Location - Gurugram,Bengaluru,Hyderabad,Pune,Noida,India

We are seeking a highly analytical Quantitative Research Analyst to join our AIF Quant Fund team. The ideal candidate brings strong buy-side experience in systematic investment strategies and will play a key role in developing, implementing, and maintaining sophisticated quantitative models that drive our alternative investment approach. About the Role: The Quantitative Research Analyst will be responsible for various key responsibilities that include model development, data infrastructure management, strategy testing, risk management, and technology automation. Responsibilities: Model Development & Research: Design and build multi-factor models for equity, fixed income, and alternative asset classes Develop alpha generation signals and systematic trading strategies across multiple time horizons Research and implement new quantitative factors using academic literature and market insights Enhance existing models through continuous performance monitoring and iterative improvements Data Infrastructure & Analytics: Manage large-scale financial datasets using Snowflake, SQL, and cloud-based platforms Build automated data pipelines for real-time and historical market data processing Ensure data quality, integrity, and optimize query performance for research workflows Develop efficient storage solutions for multi-asset research environments Strategy Testing & Validation: Conduct comprehensive backtesting across multiple market cycles using robust statistical methods Perform out-of-sample testing, walk-forward analysis, and Monte Carlo simulations Generate detailed performance attribution and risk decomposition analysis Document model assumptions, limitations, and validation results Risk Management & Monitoring: Build risk management frameworks including VaR, stress testing, and scenario analysis Monitor portfolio exposures, concentration risks, and factor loadings in real-time Develop automated alerting systems for model degradation and performance anomalies Support portfolio optimization and construction processes Technology & Automation: Develop Python-based research and production systems with focus on scalability Create automated model monitoring, reporting, and alert generation frameworks Collaborate on technology infrastructure decisions and platform evaluations Maintain code quality and documentation standards Qualifications: Professional Experience: 4–8 years of buy-side quantitative research in asset management, hedge funds, or proprietary trading Proven track record in systematic investment strategy development and implementation Experience with institutional-grade quantitative research and portfolio management Technical Proficiency: Programming: Advanced Python (pandas, numpy, scipy, scikit-learn, quantitative libraries) Database: Hands-on Snowflake and SQL experience with large-scale data environments Analytics: Statistical modeling, econometrics, and machine learning techniques Platforms: Bloomberg Terminal, Refinitiv, or equivalent financial data systems Quantitative Expertise: Deep understanding of factor models, portfolio optimization, and systematic risk management Knowledge of derivatives pricing, fixed income analytics, and alternative investment structures Experience with market microstructure analysis and high-frequency data processing Familiarity with performance attribution methodologies and benchmark construction Communication & Analysis: Strong problem-solving abilities with exceptional attention to detail Ability to translate quantitative insights into actionable investment recommendations Excellent presentation skills for communicating complex research to stakeholders Collaborative approach to working in cross-functional investment teams. Educational Background: Master's degree in Finance, Economics, Mathematics, Statistics, Physics, or Engineering CQF, CFA, FRM or equivalent professional certification preferred Strong academic foundation with demonstrated quantitative aptitude Regulatory Awareness: Understanding of SEBI AIF regulations and compliance frameworks Knowledge of investment management risk controls and regulatory reporting requirements Preferred Skills: Industry Recognition: Published quantitative research or contributions to investment thought leadership Multi-Asset Expertise: Experience across equity, fixed income, commodities, and alternative investments Innovation Mindset: Interest in machine learning, alternative data, and emerging quantitative techniques Advanced Programming: Proficiency in additional languages such as R, C++, or Julia; experience with version control (Git) and code optimization techniques Domain Specialization: Strong background in specific asset classes such as Indian equities & emerging markets Entrepreneurial Drive: Self-motivated individual comfortable building scalable systems from ground-up in a growing AIF technology environment Industry Certifications: Additional qualifications or specialized quantitative finance credentials will be a plus Alternative Data & AI: Experience with NLP and AI techniques for extracting investment signals from alternative text data sources (such as Filings, Analyst Reports and Transcripts) and developing reasoning-based AI models for systematic decision-making will be a plus Pay range and compensation package: Competitive with industry standards, including performance-based incentives.

Othor AI is seeking a talented and motivated Mathematician Research Intern to join our decision intelligence team. This internship offers an exceptional opportunity to work at the intersection of advanced mathematics, artificial intelligence, and real-world decision-making systems. You'll contribute to cutting-edge research that transforms how organizations make complex decisions through mathematical modeling and AI-driven insights. Key Responsibilities Develop and analyze mathematical models for decision optimization problems Research and implement novel algorithms for multi-criteria decision analysis Collaborate with AI researchers to integrate mathematical frameworks into machine learning pipelines Conduct theoretical analysis of decision intelligence algorithms and their convergence properties Prototype mathematical solutions using Python, R, or MATLAB Contribute to research publications and technical documentation Present findings to cross-functional teams and external stakeholders Assist in developing mathematical foundations for explainable AI decision systems Required Qualifications Currently pursuing or recently completed Master's or PhD in Mathematics, Applied Mathematics, Operations Research, or related field Strong background in optimization theory, linear algebra, and probability theory Experience with mathematical modeling and algorithm development Proficiency in at least one programming language (Python, R, MATLAB, or Julia preferred) Knowledge of statistical analysis and numerical methods Excellent analytical and problem-solving skills Strong written and verbal communication abilities Ability to work independently and collaboratively in a fast-paced research environment Preferred Qualifications Experience with machine learning and artificial intelligence concepts Background in game theory, decision theory, or multi-objective optimization Familiarity with deep learning frameworks (TensorFlow, PyTorch) Experience with mathematical software (Mathematica, Maple, or similar) Previous research experience in applied mathematics or related fields Publications in peer-reviewed journals or conferences Knowledge of reinforcement learning or Bayesian methods What We Offer Mentorship from leading researchers in decision intelligence and AI Opportunity to work on challenging, real-world mathematical problems Access to cutting-edge computational resources and research tools Collaborative environment with opportunities for professional growth Competitive internship compensation Potential for publication opportunities and conference presentations Flexible hybrid work arrangements Networking opportunities within the AI and decision science community Duration & Commitment 3-6 month internship with potential for extension Full-time commitment (40 hours/week) preferred Part-time arrangements considered for exceptional candidates Start date flexible based on candidate availability About Othor AI Othor AI is at the forefront of decision intelligence, developing AI systems that help organizations make better decisions through advanced mathematical modeling and machine learning. Our multidisciplinary team combines expertise in mathematics, computer science, and domain-specific knowledge to solve complex real-world problems.

The candidate should have experience in AI Development including experience in developing, deploying, and optimizing AI and Generative AI solutions. The ideal candidate will have a strong technical background, hands-on experience with modern AI tools and platforms, and a proven ability to build innovative applications that leverage advanced AI techniques. You will work collaboratively with cross-functional teams to deliver AI-driven products and services that meet business needs and delight end-users. Key Prerequisites  Experience in AI and Generative AI Development  Experience in Design, develop, and deploy AI models for various use cases, such as predictive analytics, recommendation systems, and natural language processing (NLP).  Experience in Building and fine-tuning Generative AI models for applications like chatbots, text summarization, content generation, and image synthesis.  Experience in implementation and optimization of large language models (LLMs) and transformer-based architectures (e.g., GPT, BERT).  Experience in ingestion and cleaning of data  Feature Engineering and Data Engineering  Experience in Design and implementation of data pipelines for ingesting, processing, and storing large datasets.  Experience in Model Training and Optimization  Exposure to deep learning models and fine-tuning pre-trained models using frameworks like TensorFlow, PyTorch, or Hugging Face.  Exposure to optimization of models for performance, scalability, and cost efficiency on cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI).  Hands-on experience in monitoring and improving model performance through retraining and evaluation metrics like accuracy, precision, and recall. AI Tools and Platform Expertise  OpenAI, Hugging Face  MLOps tools  Generative AI-specific tools and libraries for innovative applications. Technical Skills 1. Strong programming skills in Python (preferred) or other languages like Java, R, or Julia. 2. Expertise in AI frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face. 3. Proficiency in working with transformer-based models (e.g., GPT, BERT, T5, DALL-E). 4. Experience with cloud platforms (AWS, Azure, Google Cloud) and containerization tools (Docker, Kubernetes). 5. Solid understa

Position title: Data Science & AI Engineer Experience:6-8 years Budget:25-28 LPA Notice period : 1 Month -Immediate joiner Skills set : MLOPS,Gen AI,SLM,LLM,Python , Data science , ai engineer Roles and responsibilities: Develop, implement, and optimize machine learning models and AI algorithms to solve complex business problems. Design, build, and fine-tune AI models, particularly focusing on LLMs and SLMs, using state-of-the-art techniques and architectures Apply advanced techniques in prompt engineering, model fine-tuning, and optimization to tailor models for specific business needs. Deploy and manage machine learning models and pipelines on cloud platforms (AWS, GCP, Azure, etc.). Work closely with clients to understand their data and AI needs and provide tailored solutions. Collaborate with cross-functional teams to integrate AI solutions into broader software architectures. Mentor junior team members and provide guidance in implementing best practices in data science and AI development. Stay up-to-date with the latest trends and advancements in data science, AI, and cloud technologies. Requirement: 5+ years of experience in data science, machine learning, and AI technologies. Proven experience working with cloud platforms such as Google Cloud, Microsoft Azure, or AWS. Expertise in programming languages such as Python, R, Julia, and AI frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging face Transformers. Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Tableau) Solid understanding of data engineering concepts including ETL, data pipelines, and databases (SQL, NoSQL). Experience with MLOps practices and deployment of models in production environments. Familiarity with NLP (Natural Language Processing) tasks and working with large-scale datasets. Hands-on experience with generative AI models like GPT, Gemini, Claude, Mistral etc. Client-facing experience with strong communication skills to manage and engage stakeholders. Strong problem-solving skills and analytical mindset. Ability to work independently and as part of a team and mentor and provide technical leadership to junior team members

Lead Sofware Engineer - Simulations(with ML Background) - Global Data Analytics, Technology (Maersk) This position will be based in India – Bangalore/Pune A.P. Moller - Maersk A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains. Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too. The Brief We are seeking a Lead Software Engineer with deep experience in simulation systems and a solid foundation in machine learning to lead the architecture and development of our next-generation simulation and digital twin platforms. This role blends technical leadership with hands-on engineering, guiding the design of simulation systems that model real-world environments and power intelligent, ML-driven decision-making. You’ll be responsible for leading simulation efforts that generate actionable insights, synthetic data, and predictive capabilities — while also influencing how ML models are built, trained, and deployed within these environments. What I'll be doing – your accountabilities/responsibilities? Architect and lead simulation platforms that model complex systems across time, agents, and interactions. Bridge simulation systems with ML workflows: data generation, model training/testing, reinforcement learning, etc. Define system architecture, technology choices, and software patterns for scalable, high-performance simulation and ML integration. Collaborate with ML engineers, data scientists, and domain experts to enable closed-loop simulations for forecasting, optimization, and control. Lead cross-functional engineering efforts across simulation, data, and ML infrastructure teams. Mentor engineers across disciplines, setting technical standards and fostering a high-performance culture. Own end-to-end delivery of simulation-enabled intelligent systems — from ideation to production. Develop and optimize algorithms for discrete-event simulation, agent-based modeling. Support scenario testing, what-if analysis, and optimization workflows using simulation outputs. Ensure models are modular, extensible, and easily integrated with external services/platforms (e.g., dashboards, analytics, AI agents). Foundational /Must Have Skills Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field. 12+ years of software engineering experience, with 3+ years leading teams or major initiatives. Demonstrated experience in simulation platforms (e.g., SimPy, Mesa, CARLA, Unity, AnyLogic, or custom-built engines). Strong programming skills in Python (required); additional languages like C++, Rust, or Julia are a plus. Deep understanding of ML principles — model pipelines, data engineering, evaluation, and deployment. Experience working with synthetic data, simulators for ML training/testing, or RL environments (e.g., OpenAI Gym, Isaac Sim, Unity ML-Agents). Solid grasp of software architecture, distributed systems, and CI/CD pipelines. Preferred To Have Experience with reinforcement learning, decision-making under uncertainty, or control systems. Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and MLOps tools (e.g. MLflow, Weights & Biases). Background in simulation-heavy domains such as robotics, logistics, autonomous systems. Familiarity with cloud infrastructure (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Strong communication and cross-functional leadership skills — able to align engineers, ML teams, and product stakeholders. As a performance-oriented company, we strive to always recruit the best person for the job – regardless of gender, age, nationality, sexual orientation or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high-performing teams. Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.

Key Responsibilities: Develop and expand model libraries for JuliaSim, particularly in mechanical, hydraulic, thermal, and electrical domains. Build digital twins for systems such as HVACs, batteries, vehicles, and other industry-relevant applications. Collaborate with industry experts to gather and understand customer requirements and integrate them into model development. Work with Git-based workflows and utilize test-driven development and CI/CD pipelines for efficient and high-quality software development. Required Qualifications: Domain knowledge in either Mechanical, Electrical, or Chemical engineering fields. Experience using numerical solvers to build and solve 1D models. Proven experience with acausal domain modeling tools such as Modelica, Simscape, Amesim, or/and GPROMs. Proficiency in Git-based workflows, test-driven development, and working with CI/CD pipelines. Knowledge of numerical computing with experience in Julia, Matlab, Python, or Fortran, etc. Preferred Qualifications: Experience with Julia, SciML, DifferentialEquations.jl and ModelingToolkit.jl to develop scalable and high-performance models. Experience in Controls and Optimization.

Job Description Responsibilities : Identify relevant data sources - a combination of data sources to make it useful. Build the automation of the collection processes. Pre-processing of structured and unstructured data, leveraging NLP techniques for text data. Handle large amounts of information to create the input for analytical models, incorporating Gen AI for advanced data processing and generation. Build predictive models, machine learning, and deep learning algorithms; innovate with Gen AI applications in model development. Build network graphs, apply NLP techniques for text analysis, and design forecasting models while building data pipelines for end-to-end solutions. Propose solutions and strategies to address business challenges, integrating Gen AI and NLP in practical applications. Collaborate with product development teams and communicate with Senior Leadership teams. Participate in problem-solving sessions, leveraging NLP and Gen AI for innovative solutions. Requirements Bachelor's degree in a highly quantitative field (e., Computer Science, Engineering, Physics,Math, Operations Research, etc.) or equivalent experience. Extensive machine learning and algorithmic background with deep expertise in Gen AI andNatural Language Processing (NLP) techniques, along with a strong understanding of supervised and unsupervised learning methods, reinforcement learning, deep learning, Bayesian inference, and network graph analysis. Advanced knowledge of NLP methods, including text generation, sentiment analysis, namedentity recognition, and language modelling. Strong math skills, including proficiency in statistics, linear algebra, and probability, with the ability to apply these concepts in Gen AI and NLP solutions. Proven problem-solving aptitude with the ability to apply NLP and Gen AI tools to real-world business challenges. Excellent communication skills with the ability to translate complex technical information, especially related to Gen AI and NLP, into clear insights for non-technical stakeholders. Fluency in at least one data science/analytics programming language (e., Python, R, Julia), with expertise in NLP and Gen AI libraries like TensorFlow, PyTorch, Hugging Face, or OpenAI tools. Start-up experience is a plus, with ideally 5-8 years of advanced analytics experience in startups or marquee companies, particularly in roles leveraging Gen AI and NLP for product or business innovations. (ref:hirist.tech)

AI/ML Engineer – Core Algorithm and Model Expert 1. Role Objective: The engineer will be responsible for designing, developing, and optimizing advanced AI/ML models for computer vision, generative AI, Audio processing, predictive analysis and NLP applications. Must possess deep expertise in algorithm development and model deployment as production-ready products for naval applications. Also responsible for ensuring models are modular, reusable, and deployable in resource constrained environments. 2. Key Responsibilities: 2.1. Design and train models using Naval-specific data and deliver them in the form of end products 2.2. Fine-tune open-source LLMs (e.g. LLaMA, Qwen, Mistral, Whisper, Wav2Vec, Conformer models) for Navy-specific tasks. 2.3. Preprocess, label, and augment datasets. 2.4. Implement quantization, pruning, and compression for deployment-ready AI applications. 2.5. The engineer will be responsible for the development, training, fine-tuning, and optimization of Large Language Models (LLMs) and translation models for mission-critical AI applications of the Indian Navy. The candidate must possess a strong foundation in transformer-based architectures (e.g., BERT, GPT, LLaMA, mT5, NLLB) and hands-on experience with pretraining and fine-tuning methodologies such as Supervised Fine-Tuning (SFT), Instruction Tuning, Reinforcement Learning from Human Feedback (RLHF), and Parameter-Efficient Fine-Tuning (LoRA, QLoRA, Adapters). 2.6. Proficiency in building multilingual and domain-specific translation systems using techniques like backtranslation, domain adaptation, and knowledge distillation is essential. 2.7. The engineer should demonstrate practical expertise with libraries such as Hugging Face Transformers, PEFT, Fairseq, and OpenNMT. Knowledge of model compression, quantization, and deployment on GPU-enabled servers is highly desirable. Familiarity with MLOps, version control using Git, and cross-team integration practices is expected to ensure seamless interoperability with other AI modules. 2.8. Collaborate with Backend Engineer for integration via standard formats (ONNX, TorchScript). 2.9. Generate reusable inference modules that can be plugged into microservices or edge devices. 2.10. Maintain reproducible pipelines (e.g., with MLFlow, DVC, Weights & Biases). 3. Educational Qualifications Essential Requirements: 3.1. B Tech / M.Tech in Computer Science, AI/ML, Data Science, Statistics or related field with exceptional academic record. 3.2. Minimum 75% marks or 8.0 CGPA in relevant engineering disciplines. Desired Specialized Certifications: 3.3. Professional ML certifications from Google, AWS, Microsoft, or NVIDIA 3.4. Deep Learning Specialization. 3.5. Computer Vision or NLP specialization certificates. 3.6. TensorFlow/ PyTorch Professional Certification. 4. Core Skills & Tools: 4.1. Languages: Python (must), C++/Rust. 4.2. Frameworks: PyTorch, TensorFlow, Hugging Face Transformers. 4.3. ML Concepts: Transfer learning, RAG, XAI (SHAP/LIME), reinforcement learning LLM finetuning, SFT, RLHF, LoRA, QLorA and PEFT. 4.4. Optimized Inference: ONNX Runtime, TensorRT, TorchScript. 4.5. Data Tooling: Pandas, NumPy, Scikit-learn, OpenCV. 4.6. Security Awareness: Data sanitization, adversarial robustness, model watermarking. 5. Core AI/ML Competencies: 5.1. Deep Learning Architectures: CNNs, RNNs, LSTMs, GRUs, Transformers, GANs, VAEs, Diffusion Models 5.2. Computer Vision: Object detection (YOLO, R-CNN), semantic segmentation, image classification, optical character recognition, facial recognition, anomaly detection. 5.3. Natural Language Processing: BERT, GPT models, sentiment analysis, named entity recognition, machine translation, text summarization, chatbot development. 5.4. Generative AI: Large Language Models (LLMs), prompt engineering, fine-tuning, Quantization, RAG systems, multimodal AI, stable diffusion models. 5.5. Advanced Algorithms: Reinforcement learning, federated learning, transfer learning, few-shot learning, meta-learning 6. Programming & Frameworks: 6.1. Languages: Python (expert level), R, Julia, C++ for performance optimization. 6.2. ML Frameworks: TensorFlow, PyTorch, JAX, Hugging Face Transformers, OpenCV, NLTK, spaCy. 6.3. Scientific Computing: NumPy, SciPy, Pandas, Matplotlib, Seaborn, Plotly 6.4. Distributed Training: Horovod, DeepSpeed, FairScale, PyTorch Lightning 7. Model Development & Optimization: 7.1. Hyperparameter tuning using Optuna, Ray Tune, or Weights & Biases etc. 7.2. Model compression techniques (quantization, pruning, distillation). 7.3. ONNX model conversion and optimization. 8. Generative AI & NLP Applications: 8.1. Intelligence report analysis and summarization. 8.2. Multilingual radio communication translation. 8.3. Voice command systems for naval equipment. 8.4. Automated documentation and report generation. 8.5. Synthetic data generation for training simulations. 8.6. Scenario generation for naval training exercises. 8.7. Maritime intelligence synthesis and briefing generation. 9. Experience Requirements 9.1. Hands-on experience with at least 2 major AI domains. 9.2. Experience deploying models in production environments. 9.3. Contribution to open-source AI projects. 9.4. Led development of multiple end-to-end AI products. 9.5. Experience scaling AI solutions for large user bases. 9.6. Track record of optimizing models for real-time applications. 9.7. Experience mentoring technical teams 10. Product Development Skills 10.1. End-to-end ML pipeline development (data ingestion to model serving). 10.2. User feedback integration for model improvement. 10.3. Cross-platform model deployment (cloud, edge, mobile) 10.4. API design for ML model integration 11. Cross-Compatibility Requirements: 11.1. Define model interfaces (input/output schema) for frontend/backend use. 11.2. Build CLI and REST-compatible inference tools. 11.3. Maintain shared code libraries (Git) that backend/frontend teams can directly call. 11.4. Joint debugging and model-in-the-loop testing with UI and backend teams

Job description Experienced AI/ML Engineer with expertise in Machine Learning, Deep Learning, NLP, and Generative AI. strong expertise in LLMs, Retrieval-Augmented Generation (RAG), Agentic AI, and MLOps to develop scalable and production-ready AI solutions. Key Responsibilities: Develop & Optimize AI/ML Solutions: Build and deploy LLMs, RAG, Agentic AI, and GenAI applications. ML Pipeline Development: Implement and automate scalable ML pipelines using MLflow, AWS SageMaker, Databricks, and PySpark. MLOps Implementation: Establish CI/CD workflows, model versioning, monitoring, and automated retraining. Cloud & Infrastructure: Leverage AWS AI/ML services (Sagemaker, Bedrock, Lambda, Step Functions, ECS/EKS) for scalable AI solutions. Data Engineering with PySpark: Optimize large-scale ETL workflows, data pipelines, and distributed data processing. LLMs & RAG Applications: Fine-tune and deploy LLMs integrated with vector databases (FAISS, Pinecone, ChromaDB). NLP & Deep Learning: Work with transformers, embeddings, multi-modal AI models, and text processing frameworks. Orchestration & Containerization: Deploy and manage AI workloads using Kubernetes (EKS), Docker, and CI/CD pipelines.Senior Data Engineer with special emphasis and experience of 10 to 12 years of IT and 6 to 8 years of experience on Artificial Intelligence, Deep learning and Machine Learning. bachelor degree in computer science engineering or related field. Able to Lead AI/ML team and working closely with all the team members and client. Strong Hands on Experience on Python coding and all the python and Data science libraries. Manage and direct processes and R&D (research and development) to meet the needs of our AI strategy. Understand company and client challenges and how integrating AI capabilities can help lead to solutions As a Machine Learning Engineer, you will play a crucial role in the development and implementation of cutting-edge artificial intelligence products. Hands on experience on all AWS service. Lead cross-functional teams in identifying and prioritizing key areas of a partner business where AI solutions can drive significant business benefit Analyse and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards Strong Hands-on experience on SQL queries, CICD Pipelines, Kubernetes etc.,

Job Information Date Opened 07/22/2025 Job Type Permanent RSD NO 11146 Industry IT Services Min Experience 6 Max Experience 8 City Chennai State/Province Tamil Nadu Country India Zip/Postal Code 600018 Job Description Job Title - BlackRock Aladdin Specialist Location - Chennai, Bangalore, Hyderabad Job Type - Full-time - Work from office Position Overview - As a BlackRock Aladdin Specialist at Indium, you will play a crucial role in supporting & enhancing the Aladdin platform for our clients in the financial sector. You will collaborate with cross-functional teams to implement and customize Aladdin solutions, ensuring seamless integration and optimal performance. Responsibilities – Understands Life of a Trade. Knowledge of Black-rock Aladdin Solution Explore to Portfolio Management, Trade Execution, Data Control and Operations and Portfolio administration on Aladdin Platform. Experience of working in an Asset Manager or similar organization with strong knowledge of order and execution management systems and electronic trading platforms is mandatory Technical Experience: 1: Experience with Black-rock Aladdin platform 2: Proven ability to use complex analytical, interpretive and problem-solving skills and techniques, to synthesize and present complex information to stakeholders of various levels 3: Demonstrated ability to manipulate, integrate and visualize complex data sets Understanding of global Asset Management and large asset owners 4: Good communication skills 5: Support Experience Aladdin Platform Customization - Configure & customize the Aladdin platform to meet the specific needs and requirements of clients. Knowledge of Julia Platform. Hence, knowledge of Python, R and Matlab are desirable. Implementation and Integration - Lead the implementation of Aladdin solutions for clients, ensuring smooth integration with existing systems. Stakeholder Management - Work closely with clients, internal teams, and other stakeholders to understand business requirements and deliver tailored Aladdin solutions. Training & Documentation - Maintain the Knowledge Base & document detailing Standard Operating Procedures (SOP), support issues, resolutions, & best practices for future reference. Qualifications - Bachelor's degree in Computer Science, Information Technology, or a related field. Proven experience working with BlackRock Aladdin, with a strong understanding of its features and capabilities. Technical proficiency in scripting languages such as Python / R / Matlab and familiarity with APIs. Excellent problem-solving skills and a proactive approach to troubleshooting. Strong communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. Relevant certifications in Aladdin or related technologies would be a plus. Experience with Amazon Web Services (AWS) – including data management, computer services, and cloud-based deployment. At Indium diversity, equity, and inclusion (DEI) are the cornerstones of our values. We champion DEI through a dedicated council, expert sessions, and tailored training programs, ensuring an inclusive workplace for all. Our initiatives, including the WE@IN women empowerment program and our DEI calendar, foster a culture of respect and belonging. Recognized with the Human Capital Award, we are committed to creating an environment where every individual thrives. Join us in building a workplace that values diversity and drives innovation.

At QpiAI, we are at the forefront of the discovery of optimal AI and Quantum systems in various industries such as Life sciences, Healthcare, Transportation, Finance, Industrial, and Space technologies. Our focus lies in building full-stack Enterprise Quantum Computers. As a part of the QpiAI Quantum hardware team, your role will involve the design and characterization of Quantum Processors, Cryogenic Quantum Control Circuits, RF Control Hardware, and QpiAI ASGP. We are currently seeking a talented engineer with a strong mathematical background and sharp algorithmic skills to join us in building a high-performance optimization infrastructure. This infrastructure will cater to real-world decision-making problems in domains like logistics, manufacturing, and emerging technologies. We need someone who excels at translating abstract optimization problems into efficient, production-ready solvers. Key Responsibilities - Design and implement fast, scalable solvers for complex optimization problems in both discrete and continuous domains. - Develop constraint modeling frameworks and metaheuristic algorithms based on solid mathematical principles. - Evaluate solution quality, convergence behavior, and performance benchmarks across various instances and datasets. - Collaborate with system engineers to seamlessly integrate your solver modules into larger optimization stacks and real-time decision systems. - Explore and incorporate techniques from mathematical programming, stochastic methods, and quantum-inspired approaches. What We're Looking For - Strong mathematical foundation including expertise in linear algebra, combinatorics, graph theory, numerical methods, convex and discrete optimization. - Proficiency in algorithmic and systems thinking, with the ability to write efficient, optimized code and address performance bottlenecks. - Exceptional programming skills in Python and C++ (or Rust/Julia); familiarity with low-level optimizations and profiler-driven development is advantageous. - Experience in algorithm design for constraint systems, heuristics, and metaheuristics. - Hands-on coding experience with a notable presence on platforms like Leetcode, Codeforces, or Hackerrank. - Product-oriented mindset with the capability to design modular, reusable, and scalable solvers suitable for production systems. - Exposure to quantum computing or hybrid quantum-classical paradigms is a bonus. Good to Have - Familiarity with model encoding techniques and constraint representations. - Experience in benchmarking on large-scale combinatorial datasets. - Participation in mathematical modeling competitions such as INMO, COMAP, or Kaggle competitions involving optimization. Why Join Us By joining our team, you will collaborate closely with professionals who view optimization not just as a mathematical puzzle but as an engineering challenge. If you are passionate about developing fast solvers, exploring boundaries in hybrid or hardware-accelerated optimization, and tackling problems at scale, we would be thrilled to have you onboard.,

Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network. Come join us to create what’s next. Let’s define tomorrow, together. Description At United, we have some of the best aircraft in the world. Our Technical Operations team is full of aircraft maintenance technicians, engineers, planners, ground equipment and facilities professionals, and supply chain teams that help make sure they’re well taken care of and ready to get our customers to their desired destinations. If you’re ready to work on our planes, join our Tech Ops experts and help keep our fleet in tip-top shape. Job Overview And Responsibilities The Manager - Inventory Management manages provisioning and inventory planning of expendable parts and rotable parts to support the maintenance operation of United Airlines fleets. This includes planning of inventory investment and optimal inventory levels to adequately support maintenance needs. Continuously monitors the performance of the inventory plans. Accountable for identifying automation and integration opportunities to improve efficiency and support organizational goals. Develop strategic and tactical inventory plans for rotable and expendable parts to support the expected changes in schedule and maintenance operations Manage the team in making daily strategic adjustments to station inventory levels for rotable and expendable parts to support the maintenance operations This includes, but not limited to, analyzing and establishing system service levels that support operations at the least total cost, adjusting allocations/ROPs to support service levels with expected flying and maintenance changes, being accountable for life cycle of inventory – inception through final disposition and being accountable for performance against plan Identify supply chain planning automation opportunities in collaboration with other teams in the organization Develop project plans and ensure timely project completions Mentor team to develop in their roles and skillsets This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded. This position is for United Airlines Business Services Pvt. Ltd - a wholly owned subsidiary of United Airlines Inc. Qualifications What’s needed to succeed (Minimum Qualifications): BS degree in a quantitative field such as engineering, supply chain management or related field Understanding of supply chain operations, planning and management Exhibits an analytical approach to problem solving with attention to detail and a sense of urgency 5+ years of relevant experience in an analytics or process improvement-oriented role in supply chain, aviation, manufacturing or related industry Understanding of supply chain functions including sourcing/procurement, vendor management, inventory planning, warehousing and logistics Familiarity with Line and Base maintenance planning and operations Knowledge of relational database models and SQL Familiarity with Supply Chain models Strong written and verbal communication skills Experience with automation and digital technology deployments Ability to identify automation and supply chain optimization opportunities in existing processes to improve efficiency Must be legally authorized to work in India for any employer without sponsorship Must be fluent in English (written and spoken) Successful completion of interview required to meet job qualification Reliable, punctual attendance is an essential function of the position What will help you propel from the pack (Preferred Qualifications): MS degree in a quantitative field such as math, statistics and/or MBA Lean Six Sigma Green/Black Belt certification Project management experience Experience with continuous improvement methodologies Experience using statistical and mathematical methods Experience in inventory management Experience in a related field involving automation of complex business processes Experience leading direct reports Familiarity with ERP capabilities At least two years of airline experience At least two years of supply chain experience Strong background in one or more supply chain functions Familiarity with Maintenance, Repair and Overhaul (MRO) functions Familiarity with the airline industry Background in agile project management methodologies Strong understanding of Supply Chain Planning tools Familiarity with Line and Base Maintenance Planning Familiarity with MRO planning Strong project management skills Financial and budget/expense management Ability to establish and monitor policies and guidelines Programming experience in a scripting language such as Python, R, and/or Julia GGN00002041

GenAI Engineer – CL4 Role Overview : As a GenAI Engineer , you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for Deloitte's business investments. You will leverage your extensive GenAI & engineering craftmanship across multiple programming languages and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions. Key Responsibilities : Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations. Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support. Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a learning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning. Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team : US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Qualifications : § A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. § Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc. § 5+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc. § Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc. § Proven experience with big data technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL. § Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP. § Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc. § Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. How You will Grow: At Deloitte, our professional development plans focus on helping people at every level of their career to identify and use their strengths to do their best work every day and excel in everything they do. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India. Benefits to help you thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303508

Summary Position Summary GenAI Engineer – CL4 Role Overview : As a GenAI Engineer , you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for Deloitte's business investments. You will leverage your extensive GenAI & engineering craftmanship across multiple programming languages and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions. Key Responsibilities : Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations. Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support. Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a learning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning. Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team : US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Qualifications : A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc. 5+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc. Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc. Proven experience with big data technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL. Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP. Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc. Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. How You will Grow: At Deloitte, our professional development plans focus on helping people at every level of their career to identify and use their strengths to do their best work every day and excel in everything they do. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303508

Job Overview We are seeking a Data Scientist with a strong foundation in machine learning and a passion for the travel industry. You will work with cross-functional teams to analyze customer behavior, forecast travel demand, optimize pricing models, and deploy AI-driven solutions to improve user experience and drive business growth. Key Responsibilities Engage in all stages of the project lifecycle, including data collection, labeling, and preprocessing, to ensure high-quality datasets for model training. Utilize advanced machine learning frameworks and pipelines for efficient model development, training execution, and deployment. Implement MLFlow for tracking experiments, managing datasets, and facilitating model versioning to streamline collaboration. Oversee model deployment on cloud platforms, ensuring scalable and robust performance in real-world travel applications. Analyze large volumes of structured and unstructured travel data to identify trends, patterns, and actionable insights. Develop, test, and deploy predictive models and machine learning algorithms for fare prediction, demand forecasting, and customer segmentation. Create dashboards and reports to communicate insights effectively to stakeholders across the business. Collaborate with Engineering, Product, Marketing, and Finance teams to support strategic data initiatives. Build and maintain data pipelines for data ingestion, transformation, and modeling. Conduct statistical analysis, A/B testing, and hypothesis testing to guide product decisions. Automate processes and contribute to scalable, production-ready data science tools. Technical Skills Machine Learning Frameworks: PyTorch, TensorFlow, JAX, Keras, Keras-Core, Scikit-learn, Distributed Model Training Programming & Development: Python, Pyspark, Julia, MATLAB, Git, GitLab, Docker, MLOps, CI/CD Pipelines Cloud & Deployment: AWS SageMaker, MLFlow, Production Scaling Data Science & Analytics: Statistical Analysis, Predictive Modeling, Feature Engineering, Data Preprocessing, Pandas, NumPy, PySpark Computer Vision: CNN, RNN, OpenCV, Kornia, Object Detection, Image Processing, Video Analytics Visualization Tools: Looker,Tableau, Power BI, Matplotlib, Seaborn Databases & Querying: SQL, Snowflake, Databricks Big Data & MLOps: Spark, Hadoop, Kubernetes, Model Monitoring Nice To Have Experience with deep learning, LLMs, NLP (Transformers), or recommendation systems in travel use cases. Knowledge of GDS APIs (Amadeus, Sabre), flight search optimization, and pricing models. Strong system design (HLD/LLD) and architecture experience for production-scale ML workflows. Skills: data preprocessing,docker,feature engineering,sql,python,predictive modeling,statistical analysis,keras,data science,spark,data scientist,aws sagemaker,machine learning,mlflow,tensorflow,pytorch

About Prismforce\ Prismforce is a Vertical SaaS company revolutionizing the Talent Supply Chain for global Technology, R&D/Engineering, and IT Services companies. Our AI-powered product suite enhances business performance by enabling operational flexibility, accelerating decision-making, and boosting profitability. Our mission is to become the leading industry cloud/SaaS platform for tech services and talent organizations worldwide.\ Job Description Role: Data Scientist Reporting to: Lead AI/ML Location: Mumbai/Bangalore/Pune/Kolkata Job Brief We are looking for Data Scientists to build data products to be the core of SAAS company disrupting the Skill market. You would be required to create and participate in evolving Analytical culture of the organization, experiment with the existing Analytical Techniques, Improvise on existing algorithms to solve the problems at hand, Innovate new algorithms to disrupt the industry, and play the critical role in solving the problems at hand. Responsibilities Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams Requirements Bachelor's degree in a highly quantitative field (e.g., Computer Science, Engineering, Physics, Math, Operations Research, etc.) or equivalent experience. Extensive machine learning and algorithmic background with deep expertise in Gen AI and Natural Language Processing (NLP) techniques, along with a strong understanding of supervised and unsupervised learning methods, reinforcement learning, deep learning, Bayesian inference, and network graph analysis. Advanced knowledge of NLP methods, including text generation, sentiment analysis, named entity recognition, and language modelling. Strong math skills, including proficiency in statistics, linear algebra, and probability, with the ability to apply these concepts in Gen AI and NLP solutions. Proven problem-solving aptitude with the ability to apply NLP and Gen AI tools to real-world business challenges. Excellent communication skills with the ability to translate complex technical information, especially related to Gen AI and NLP, into clear insights for non-technical stakeholders. Fluency in at least one data science/analytics programming language (e.g., Python, R, Julia), with expertise in NLP and Gen AI libraries like TensorFlow, PyTorch, Hugging Face, or OpenAI tools. Start-up experience is a plus, with ideally 5-8 years of advanced analytics experience in startups or marquee companies, particularly in roles leveraging Gen AI and NLP for product or business innovations. Required Skills Machine Learning, Deep Learning, Algorithms, Computer Science, Engineering, Operations Research, Math Skills, Communication Skills, SAAS Product, IT Services, Artificial Intelligence, ERP, Product Management, Automation, Analytical Models, Predictive Models, NLP, Forecasting Models, Product Development, Leadership, Problem Solving, Unsupervised Learning, Reinforcement Learning, Natural Language Processing, Algebra, Data Science, Programming Language, Python, Julia. What Makes Us Unique First-Mover Advantage: We are the only Vertical SaaS product company addressing Talent Supply Chain challenges in the IT services industry. Innovative Product Suite: Our solutions offer forward-thinking features that outshine traditional ERP systems. Strategic Expertise: Guided by an advisory board of ex-CXOs from top global IT firms, providing unmatched industry insights. Experienced Leadership: Our founding team brings deep expertise from leading firms like McKinsey, Deloitte, Amazon, Infosys, TCS, and Uber. Diverse and Growing Team: We have grown to 160+ employees across India, with hubs in Mumbai, Pune, Bangalore, and Kolkata. Strong Financial Backing: Series A-funded by Sequoia, with global IT companies using our product as a core solution. Why Join Prismforce Competitive Compensation: We offer an attractive salary and benefits package that rewards your contributions. Innovative Projects: Work on pioneering projects with cutting-edge technologies transforming the Talent Supply Chain. Collaborative Environment: Thrive in a dynamic, inclusive culture that values teamwork and innovation. Growth Opportunities: Continuous learning and development are core to our philosophy, helping you advance your career. Flexible Work: Enjoy flexible work arrangements that balance your work-life needs. By joining Prismforce, you'll become part of a rapidly expanding, innovative company that's reshaping the future of tech services and talent management. Perks & Benefits Work with the best in the industry: Work with a high-pedigree leadership team that will challenge you, build on your strengths and invest in your personal development Insurance Coverage-Group Mediclaim cover for self,spouse,kids and parents & Group Term Life Insurance Policy for self. Flexible Policies Retiral Benefits Hybrid Work Model Self-driven career progression tool

University: Delft University of Technology (TU Delft) Country: Netherlands Deadline: 2025-07-31 Fields: Civil Engineering, Computational Science, Mechanical Engineering, Applied Mathematics, Environmental Engineering The Department of Civil Engineering and Geosciences at Delft University of Technology (TU Delft) invites applications for a PhD position focused on the development of scalable solvers for multiscale, multiphysics, and multifidelity simulations in offshore floating solar farms. The successful candidate will join the CMOE group and contribute to the DigiOcean4Solar project, advancing scientific computing in the field of renewable energy. Key Responsibilities – Develop and analyze multiscale models for wind-wave-structure interaction in offshore floating solar farms. – Design and implement scalable solvers for large-scale high-performance computing applications. – Assess farm-scale effects in floating solar installations. Requirements – Strong background in scientific computing, numerical partial differential equations, and finite element methods. – Proficiency in programming languages such as Julia, Python, or C++, and experience with HPC libraries. – Experience or interest in multiphysics or multiscale simulation methods. – Demonstrated enthusiasm for renewable energy and/or offshore engineering applications. Benefits – Opportunity to advance scientific computing for emerging renewable energy technologies. – Collaborative research environment with international research institutions. – Membership in the CMOE research group at TU Delft. Application Procedure Interested candidates are invited to apply online at https://lnkd.in/eVhv6aHG. The position is based in Delft, Netherlands. Application deadline: 2025-07-31 Get the latest openings in your field and preferred country—straight to your email inbox. Sign up now for 14 days free: https://phdfinder.com/position-alert-service/ We’re an independent team helping students find opportunities. Found this opportunity helpful? Support us with a coffee! Also See PhD Research Fellow in the Mutual Impact of Climate Change and Offshore Renewable Energy PhD Position in Underwater Acoustics and Offshore Engineering PhD and Postdoctoral Positions in Aero/Hydro-Acoustics – ERC Project Off-coustics PhD Position in Geodesy and Satellite Radar Interferometry (InSAR) PhD Vacancies in Offshore Engineering – Underwater Acoustics and Environmental Impacts

Define, Design, and Build an optimal data pipeline architecture to collect data from a variety of sources, cleanse, and organize data in SQL & NoSQL destinations (ELT & ETL Processes). Define and Build business use case-specific data models that can be consumed by Data Scientists and Data Analysts to conduct discovery and drive business insights and patterns. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies. Build and deploy analytical models and tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics. Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs. Define, Design, and Build Executive dashboards and reports catalogs to serve decision-making and insight generation needs. Provide inputs to help keep data separated and secure across data centers on-prem and private and public cloud environments. Create data tools for analytics and data science team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Implement scheduled data load process and maintain and manage the data pipelines. Troubleshoot, investigate, and fix failed data pipelines and prepare RCA. Experience with a mix of the following Data Engineering Technologies Python, Spark, Snowflake, Databricks, Hadoop (CDH), Hive, Sqoop, oozie SQL Postgres, MySQL, MS SQL Server Azure ADF, Synapse Analytics, SQL Server, ADLS G2 AWS Redshift, EMR cluster, S3 Experience with a mix of the following Data Analytics and Visualization toolsets SQL, PowerBI, Tableau, Looker, Python, R Python libraries -- Pandas, Scikit-learn, Seaborn, Matplotlib, TF, Stat-Models, PySpark, Spark-SQL, R, SAS, Julia, SPSS, Azure Synapse Analytics, Azure ML studio, Azure Auto ML

Define, Design, and Build an optimal data pipeline architecture to collect data from a variety of sources, cleanse, and organize data in SQL & NoSQL destinations (ELT & ETL Processes). Define and Build business use case-specific data models that can be consumed by Data Scientists and Data Analysts to conduct discovery and drive business insights and patterns. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies. Build and deploy analytical models and tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics. Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs. Define, Design, and Build Executive dashboards and reports catalogs to serve decision-making and insight generation needs. Provide inputs to help keep data separated and secure across data centers - on-prem and private and public cloud environments. Create data tools for analytics and data science team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Implement scheduled data load process and maintain and manage the data pipelines. Troubleshoot, investigate, and fix failed data pipelines and prepare RCA. Experience with a mix of the following Data Engineering Technologies Python, Spark, Snowflake, Databricks, Hadoop (CDH), Hive, Sqoop, oozie SQL - Postgres, MySQL, MS SQL Server Azure - ADF, Synapse Analytics, SQL Server, ADLS G2 AWS - Redshift, EMR cluster, S3 Experience with a mix of the following Data Analytics and Visualization toolsets SQL, PowerBI, Tableau, Looker, Python, R Python libraries -- Pandas, Scikit-learn, Seaborn, Matplotlib, TF, Stat-Models, PySpark, Spark-SQL, R, SAS, Julia, SPSS, Azure - Synapse Analytics, Azure ML studio, Azure Auto ML

Job Description: Principal Data Scientist (Reinforcement Learning and Game AI) Location : Chennai Department : Data Science Reports To : CTO Please share your profile to elangovan@algosoftware.io Mission: We are seeking a Principal Data Scientist with deep expertise in Reinforcement Learning (RL) and Neural Networks to lead the evolution of our AI core for gaming applications, specifically in imperfect information games like poker. This role offers the opportunity to work on ground breaking innovations, collaborate with industry leaders, and gain visibility as a domain expert through publications and conferences. Key Responsibilities : Lead the development and evolution of our AI core, currently built in C++, towards the next generation of algorithms and architectures. The main responsibility is to lead the evolution of our AI core to the next level. Included the opportunity to get visibility as an industry expert through the publishing of papers, conferences, and so on, to make it more appealing. Design, implement, and optimize advanced RL algorithms tailored for imperfect information games. Research and integrate state-of-the-art techniques in RL, neural networks, and game theory to enhance AI performance and scalability. Collaborate with cross-functional teams to identify challenges and innovate AI-driven solutions. Evaluate and fine-tune AI models for decision-making, strategy optimization, and real-time applications in gaming. Profile, optimize, and troubleshoot the AI core for high-performance execution across different computing architectures (e.g., CPU, GPU, or custom accelerators). Document methodologies, experiments, and results to ensure transparency and reproducibility. Required Skills and Qualifications : Bachelors, Master’s, or Ph.D. in Computer Science, Mathematics, Physics, Artificial Intelligence, or a related field. 10+ years of experience in AI/ML, with a strong focus on Reinforcement Learning and Neural Networks. Proficiency in programming languages commonly used in AI, such as C++, Python, Julia, or others relevant to your expertise. In-depth understanding of game theory, especially concepts like Nash equilibrium and strategies in imperfect information games. Expertise in RL frameworks and tools like OpenSpiel, RLlib, or similar libraries tailored for game AI. Strong knowledge of RL algorithms, and experience with neural network architectures. Familiarity with parallel computing, performance profiling, and optimization techniques. Excellent problem-solving skills, with the ability to work independently and in a team. Preferred Skills : Experience with multi-agent RL or hierarchical RL in gaming contexts. Background in poker AI or similar imperfect information games. Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Knowledge of distributed systems, parallel programs, or cloud-based AI deployments. Published research or contributions to open-source AI projects in RL or game AI. What We Offer : The opportunity to work on cutting-edge AI applications in gaming and lead innovations in imperfect information games. Support for publishing research papers, presenting at conferences, and gaining visibility as a world domain expert in the field. A collaborative and intellectually stimulating work environment with a team passionate about pushing the boundaries of AI. Flexibility and resources to experiment with state-of-the-art techniques and contribute to open-source projects. Soft Skills : Effective communication for collaborating with cross-functional teams and presenting complex ideas clearly. Passion for innovation and driving the next generation of AI in gaming. Compensation & Benefits: Competitive salary commensurate with experience. Performance-based incentives tied to achieving key financial and strategic goals. Opportunities for career growth within a fast-scaling tech group.