ml engineer

DocuSketch

<div>
 
 The fastest-growing European SaaS company is searching for an
 
 AI/ML Engineer!
 
 
 
 ⚠️
 
 Before you apply:
 
 
 
 We require
 
 real 3D experience
 
 &mdash; meaning actual project work, not just listed skills. If 3D does not appear in your actual work history, this role is not for you.
 
 
 Applications that don't meet these criteria will be automatically rejected and may limit your eligibility for other DocuSketch roles.
 
 
 
 
 
 
 About DocuSketch:
 
 
 
 DocuSketch, with its European Headquarters in Potsdam, Germany, is a leading European software technology provider for the digital real estate economy. With our product brands Immoviewer and DocuSketch, we have become one of the most successful and fastest-growing software vendors in the rapidly expanding property tech sector. Our enthusiastic customer base is located across Europe and North America. DocuSketch's groundbreaking digital technology greatly facilitates real estate companies and building restoration companies to digitize, visualize, and virtualize real estate properties. Our solutions help our clients realize tremendous cost-saving potentials, process optimization, and revenue growth.
 
 
 
 
 
 You&rsquo;ll be working in a team that drives the company's AI development to develop algorithms for a variety of different use cases. This includes, e.g., working with equirectangular, phone, or satellite images to detect doors, windows, or other objects inside of buildings or finding facets on the roof. You&rsquo;ll be challenged by solving complex 3D geometry problems and working closely with our labeling team to ensure the best possible data quality.
 
 
 
 
 
 
 Responsibilities and Duties
 
 
 
 &middot; Research, train and deploy state-of-the-art machine learning models for object detection and 3D perception on equirectangular images
 
 
 &middot; Quickly prototype new ideas/technologies to create proof of concept and demos
 
 
 
 
 
 
 Qualifications
 
 
 
 &middot; Bachelor&rsquo;s Degree in Computer Science or equivalent experience
 
 
 &middot; Excellent math skills
 
 
 &middot; Experience with 3D computer vision algorithms
 
 
 &middot; Preferably 5+ years of experience developing and training machine learning models
 
 
 &middot; Strong Experience with Deep ML frameworks (PyTorch)
 
 
 &middot; Strong Experience in Python
 
 
 &middot; Self-motivated and energetic team player with a strong work ethic and cooperative attitude
 
 
 &middot; Excellent communication and organizational skills
 
 
 
 
 
 
 Plus
 
 
 
 &middot; Familiarity with building big data systems
 
 
 &middot; Training very large models using multiple GPUs in the cloud
 
 
 &middot; Experience with training machine learning models on equirectangular images
 
 
 
 
 
 We are seeking a performance-driven, high-energy personality who has several years of experience in the field. Since you will work intensely with teams from many countries, a solid command of the English language is a prerequisite. We offer attractive compensation, unlimited career opportunities, and the possibility to work in one of the most exciting software companies in the industry. Our headquarters are in Berlin, Germany, with major offices in Belgrade, Serbia, Lakeland, Florida, and in Canada.
 
 
 
 
 
 We look forward to receiving your application!
 
</div>

AI/ML Engineer

Huspy

<div>
 
 The Story So Far: We&rsquo;re Building a Global Brand in Real Estate
 
 
 
 Huspy is one of the leading property technology companies in EMEA.Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026.
 
 
 Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we&rsquo;ve entered.We&rsquo;ve raised over $140 million (Series A and Series B) from the world&rsquo;s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.
 
 
 We&rsquo;ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world&rsquo;s most traditional industries. We&rsquo;re transforming how property transactions happen &mdash; faster, smarter, and better for everyone.We&rsquo;re not slowing down.
 
 
 The question is: will you be part of what&rsquo;s next?
 
 
 
 The Main Event: What You&rsquo;ll Drive, Build, and Own
 
 
 
 <ul>
 <li>
 Real Estate Market Modeling: Build models applied to challenges such as valuation/pricing leveraging techniques from classic supervised ML to more advanced approaches.
 </li>
 <li>
 Multimodal Embeddings: Create vector representations of Real Estate entities, such as listings, combining images, text, and structured attributes to power search, matching, deduping, or recommendations.
 </li>
 <li>
 Data Analysis &amp; Experimentation: Use SQL/Python to extract, clean, and analyze data; design experiments and evaluate model-product impact with robust metrics.
 </li>
 <li>
 Model Operationalization: Ship models to production with capabilities such as monitoring, automated rollout, or CI/CD (in partnership with engineering).
 </li>
 <li>
 Cross-functional Delivery: Partner with product, engineering, and operations teams to translate business problems into scalable ML solutions.
 
 
 </li>
 </ul>
 
 The Perfect Match: What It Takes to Succeed at Huspy
 
 
 
 <ul>
 <li>
 Proven Experience: 4&ndash;8 years in applied data science/ML, delivering models that move real-world KPIs.
 </li>
 <li>
 SQL &amp; Python Mastery: Strong in frameworks such as Pandas/NumPy/Scikit-learn...building reliable data pipelines, model training and evaluation.
 </li>
 <li>
 MLOps Fundamentals: Experience deploying/maintaining models (batch or real-time), versioning, CI/CD basics, observability, and reproducible training.
 </li>
 <li>
 Communication &amp; Ownership: Clear with technical/non-technical stakeholders; can scope, prioritize, and explain tradeoffs.
 </li>
 <li>
 Comfortable with uncertainty, data quality issues, leakage risks, and market dynamics (location, seasonality, inventory shifts).
 </li>
 <li>
 Nice to Have: Software engineering experience; multimodal/vision experience; voice AI (ASR/NLU) exposure.
 </li>
 <li>
 Academic Background: Bachelor&rsquo;s in STEM (Master&rsquo;s a plus).
 
 
 </li>
 </ul>
 By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
</div>

Data Scientist

DATAMAZE . AI

<div>
 Hyderabad, India / Dubai, UAE
 
 
 Full-time
 
 
 Apply to Job
 
 
 
 About The Role
 
 
 
 We are looking for a highly motivated Machine Learning Engineer / Data Scientist to join our dynamic team. In this mid-level role, you will leverage your expertise in data science and machine learning to design, build, and deploy innovative models and solutions that address real-world challenges.
 
 
 You will collaborate with cross-functional teams, including data engineers, product managers, and software developers, to turn complex datasets into actionable insights and build machine learning solutions that drive business value. This is a fantastic opportunity to work on impactful projects, expand your skill set, and contribute to cutting-edge advancements in AI and data science.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Model Development: Design, train, and evaluate machine learning models to solve business problems such as classification, regression, clustering, and recommendation.
 </li>
 <li>
 Data Preparation: Work with large and complex datasets, performing data cleaning, preprocessing, and feature engineering to optimize model performance.
 </li>
 <li>
 Model Deployment: Deploy machine learning models into production environments, ensuring scalability and robustness.
 </li>
 <li>
 Algorithm Selection: Research and implement state-of-the-art algorithms and methodologies to enhance model accuracy and efficiency.
 </li>
 <li>
 Collaboration: Collaborate with data engineering teams to build data pipelines and ensure efficient data flow for machine learning workflows.
 </li>
 <li>
 Visualization and Reporting: Create clear and actionable visualizations and reports to communicate findings and results to stakeholders.
 </li>
 <li>
 Monitoring and Maintenance: Monitor model performance in production, address drift or bias issues, and optimize models as needed.
 </li>
 <li>
 Tool Development: Build tools and frameworks to enable rapid experimentation and iteration of machine learning models.
 </li>
 <li>
 Documentation: Maintain comprehensive documentation for models, experiments, and processes.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Education:
 
 
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field (or equivalent experience).
 
 
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Strong programming skills in Python, R, or similar languages.
 </li>
 <li>
 Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
 </li>
 <li>
 Proficiency in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
 </li>
 <li>
 Experience with big data technologies such as Spark, Hadoop, or similar.
 </li>
 <li>
 Knowledge of cloud platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure ML).
 </li>
 <li>
 Familiarity with MLOps practices and tools for CI/CD in machine learning workflows.
 </li>
 <li>
 Understanding of data visualization tools like Matplotlib, Seaborn, or Tableau.
 </li>
 <li>
 Strong grasp of statistical methods, probability, and optimization techniques.
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in machine learning, data science, or a related field.
 </li>
 <li>
 Proven experience building and deploying machine learning models in production.
 </li>
 <li>
 Experience with natural language processing (NLP), computer vision, or time-series analysis is a plus.
 
 
 </li>
 </ul>
 
 Soft Skills
 
 
 
 <ul>
 <li>
 Strong problem-solving and analytical thinking abilities.
 </li>
 <li>
 Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
 </li>
 <li>
 Ability to work independently and collaboratively within a team.
 </li>
 <li>
 Curiosity and eagerness to stay updated on the latest advancements in machine learning and AI.
 
 
 </li>
 </ul>
 
 About The Company
 
 
 
 Datamaze is a dynamic company specializing in AI, Data, and Analytics consulting services. We are dedicated to transforming businesses by leveraging the power of data and artificial intelligence. With a team of industry experts in technology, business strategy, and data science, Datamaze offers a range of services including data strategy development, AI model creation, advanced analytics, and data visualization. Our approach is client-centric, focusing on creating customized solutions that address unique business challenges and objectives. The team, comprising data scientists, AI experts, strategists, and engineers, is committed to continuous learning and innovation.
 
 
 Datamaze positions itself as a trusted partner for businesses looking to navigate the complex data and AI landscape, aiming to optimize operations, inform decision-making, and maintain a competitive edge.
 
 
 Apply Now
</div>

Machine Learning Engineer / Data Scientist (Mid-Level)

Cohere

<div>
 
 Who are we?
 
 
 
 Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
 
 
 We&rsquo;re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
 
 
 We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!
 
 
 
 Why this role?
 
 
 
 As a Member of Technical Staff on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models.
 
 
 You&rsquo;ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You&rsquo;ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally!
 
 
 
 As a Senior Member Of Technical Staff, You Will
 
 
 
 <ul>
 <li>
 Plan and execute large-group projects that carry through from ideation to production.Bring cross-functional alignment across engineering, product and other disciplines.
 </li>
 <li>
 Mentor a distributed team of engineers in subject matter expertise. Identify opportunities and gaps in existing models and strategize what to work on.
 </li>
 <li>
 Work closely with product teams to develop solutions.
 </li>
 <li>
 Engage in collaborations with our partner organizations.
 </li>
 <li>
 Assist our legal teams with preparation of patents on developed IP.
 </li>
 <li>
 Join us at a pivotal moment, shape what we build and wear multiple hats!
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 Prior experience in leading ML teams in applied research and production.
 </li>
 <li>
 Prior experience in setting as well as executing technical direction to build new or to refine existing products.
 </li>
 <li>
 Prior experience in working cross-discipline in matrixed organizations.
 </li>
 <li>
 Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
 </li>
 <li>
 Experience using large-scale distributed training and inference.
 </li>
 <li>
 Strong mentorship, communication, and problem-solving skills.
 </li>
 <li>
 A demonstrated passion for applied ML models and products.
 </li>
 <li>
 Working proficiency in Arabic.
 </li>
 <li>
 Bonus: experience working for B2B companies in the ML space.
 </li>
 <li>
 This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere.
 
 
 </li>
 </ul>
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 <ul>
 <li>
 A weekly lunch stipend of $75/&pound;75 or equivalent in your local currency for lunch.
 </li>
 <li>
 Full health and dental benefits, including a separate budget for mental health.
 </li>
 <li>
 RRSP matching, 401K, Pension Scheme.
 </li>
 <li>
 100% Parental Leave top-up for up to 6 months, for either parent.
 </li>
 <li>
 Annual enrichment benefits:
 
 
 </li>
 </ul>
 Arts &amp; culture, fitness/wellness, quality time, and a workspace improvement credit.
 
 
 Education &amp; learning stipend for conferences, courses, and coaching.
 
 
 <ul>
 <li>
 6 weeks of paid vacation (30 working days!)
 </li>
 <li>
 Budget for traveling to other offices if you are remote, plus an annual company offsite.
 
 
 </li>
 </ul>
 
 How And Where We Work
 
 
 
 <ul>
 <li>
 Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
 </li>
 <li>
 For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
 </li>
 <li>
 For those not near an office: a co-working benefit so you can work alongside others in your city.
 </li>
 <li>
 Everyone receives a $500 home office stipend to set up your workspace properly.
 
 
 </li>
 </ul>
 If any of the above doesn&rsquo;t line up exactly with your experience, we still encourage you to apply.
 
 
 We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
</div>

Senior Member of Technical Staff, MLE (Middle East)

Dezzex

Who we are?Dezzex uses Artificial Intelligence and Machine Learning technologies to advance the motor insurance industry by creating a system to automate claims. We use these technologies to improve insurance processes, reduce operational costs and enable a seamless customer experience. Our solution offering is also designed for the insurance companies, Insurance companies, Smart cities application.For applying as a Sr. Machine Learning Engineer, the person should have overall 7-8 years of experience out of which 4-5 years of experience should be in Machine &amp; Deep Machine learning. Especially using Convolution Neural Network (CNN), Image Analytics TensorFlow, Open CV etc.For applying as just a data scientist (Junior), the person needs to have experience of 3 - 9 years.With our fast-growing data scientist's team, we are looking to hire self-motivated smart individuals who are willing to take challenges in the field of Al image &amp; video analytics &amp; machine learning.Responsibilities:The Machine &amp; Deep Machine Learning Software Engineer (Expertise in Computer Vision) will be an early member of a growing team with responsibilities for designing and developing highly scalable machine learning solutions that impact many areas of our business.The individual in this role will help in the design and development of Neural Network (especially Convolution Neural Networks) &amp; ML solutions based on our reference architecture which is underpinned by big data &amp; cloud technology, micro-service architecture and high performing compute infrastructure.Typical daily activities include contributing to all phases of algorithm development including ideation, prototyping, design, and development production implementation.Required Skills:An ideal candidate will have background in software engineering and data science with expertise in machine learning algorithms, statistical analysis tools, and distributed systems.Experience in building machine learning applications, and broad knowledge of machine learning APIs, tools, and open source librariesStrong coding skills and fundamentals in data structures, predictive modelling and big data concepts Experience in designing full stack ML solutions in a distributed compute environmentExperience working with Python, Tensor Flow, Kera's, Sci-kit, pandas, NumPy, AZURE, AWS GPU Excellent communication skills with multiple levels of the organizationPay: AED10,000.00 - AED20,000.00 per monthExperience:<ul><li>ML: 3 years (Required)</li><li>Development: 5 years (Required)</li></ul>Language:<ul><li>Arabic (Preferred)</li></ul>Work Location: In person

Sr. Machine learning engineer.

Tata Consultancy Services

<div>
 
 
 Job Title
 
 &ndash; AI Engineer
 
 
 
 Company
 
 &ndash; TCS (MEA)
 
 
 
 Location
 
 &ndash; Dubai
 
 
 
 Job type
 
 &ndash; Full time
 
 
 
 
 
 
 About Us:
 
 
 
 Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world&rsquo;s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile&trade; delivery model, recognized as a benchmark of excellence in software development.
 
 
 A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world&rsquo;s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.
 
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 
 
 
 Key Accountabilities:
 
 
 <ul>
 <li>
 
 AI Solution Design &amp; Development:
 
 </li>
 <li>
 Design, build, and deploy AI-powered applications using Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services (Speech, Vision, Language), Azure AI Search, Azure Functions, and Azure Databricks.
 </li>
 <li>
 
 LLM Integration &amp; Generative AI:
 
 </li>
 <li>
 Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints (GPT-4.1, GPT-4o, GPT-4o-mini) routed through FAB's centralized AI Hub gateway for governance, observability, and capacity management. Build enterprise use cases such as knowledge search, document intelligence, content summarization, call analytics, sentiment analysis, and workflow automation.
 </li>
 <li>
 
 Python Engineering &amp; Backend Development:
 
 </li>
 <li>
 Write clean, modular, and production-grade Python code for AI/ML model development, API integrations, data processing pipelines, backend services, and automation workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, and FastAPI.
 </li>
 <li>
 
 RAG &amp; Semantic Retrieval:
 
 </li>
 <li>
 Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector search, semantic retrieval architectures, prompt engineering, and evaluation techniques for enterprise knowledge mining and document intelligence.
 </li>
 <li>
 
 Agentic AI Development:
 
 </li>
 <li>
 Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution, and orchestration across enterprise systems using FAB's GERNAS OS platform and Agent Development Kit (ADK) in a secure and governed manner.
 </li>
 <li>
 
 Model Evaluation &amp; Responsible AI:
 
 </li>
 <li>
 Implement model evaluation metrics for accuracy, hallucination detection, bias, latency, and throughput in alignment with FAB's Responsible AI framework. Ensure AI solutions comply with FAB's security, data privacy, model governance, and regulatory requirements, including controls for accuracy, hallucination, bias, latency, and resilience.
 </li>
 <li>
 
 Deployment &amp; Production Operations:
 
 </li>
 <li>
 Deploy, monitor, and optimize AI solutions in production environments using CI/CD practices, containerization, observability, logging, performance monitoring, and cost optimization techniques.
 </li>
 <li>
 
 Collaboration &amp; Stakeholder Engagement:
 
 </li>
 <li>
 Collaborate with data scientists, platform engineers, DevOps/MLOps engineers, business analysts, and product teams to convert business requirements into scalable AI solutions.
 </li>
 <li>
 
 Innovation &amp; Continuous Learning:
 
 </li>
 <li>
 Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities and recommend practical adoption opportunities aligned with FAB's AI strategy. Stay abreast of state-of-the-art developments in generative AI and agentic architectures.
 </li>
 </ul>
 
 
 
 
 
 TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory
 
 
 
 
 Azure AI Services:
 
 Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks.
 
 
 
 Python Programming:
 
 Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI).
 
 
 
 LLM &amp; Generative AI:
 
 Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques.
 
 
 
 ML Libraries &amp; Frameworks:
 
 Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK).
 
 
 
 Vector Databases:
 
 Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone.
 
 
 
 DevOps/MLOps:
 
 Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights.
 
 
 
 Cloud Security &amp; Integration:
 
 Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns.
 
 
 
 AI Ethics &amp; Governance:
 
 Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems.
 
 
 
 
 
 
 KNOWLEDGE, SKILLS, &amp; EXPERIENCE
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred.
 
 
 
 
 Minimum Experience:
 
 
 
 
 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments.
 
 
 Mandatory hands-on experience with Microsoft Azure AI Services.
 
 
 Experience working with large-scale datasets and real-time enterprise data.
 
 
 Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.
 
 
 
 
 Knowledge and Skills:
 
 
 
 
 
 Business Understanding:
 
 
 
 Strong understanding of business processes and the ability to identify opportunities for AI-driven optimization and automation across banking domains.
 
 
 
 Analytical &amp; Problem-Solving:
 
 
 
 Excellent analytical, problem-solving, debugging, and performance optimization skills with the ability to troubleshoot AI applications in production and translate complex business problems into AI solutions.
 
 
 
 Communication Skills:
 
 
 
 Strong verbal and written communication skills, capable of explaining complex AI concepts to both technical and non-technical stakeholders.
 
 
 
 Collaboration:
 
 
 
 Proven ability to work effectively in cross-functional teams, collaborating with data scientists, platform engineers, DevOps engineers, business analysts, and product teams.
 
 
 
 Responsible AI Mindset:
 
 
 
 Understanding of AI governance, model risk, data privacy, security, and compliance requirements in a regulated banking environment.
 
 
 
 Production Engineering:
 
 
 
 Ability to build, deploy, monitor, and optimize production-grade AI systems with attention to reliability, scalability, cost, and operational excellence.
 
 
 
 Adaptability &amp; Learning:
 
 
 
 Willingness to stay updated on the latest AI technologies, agentic frameworks, and cloud services, and the ability to apply them to solve evolving business challenges.
 
 
 Thank you for your interest in applying for this position with TCS. We will review your application and will get back to you if we are considering your interest in this opportunity.
 
 
 
 
 
 
 Application Deadline: 30- July -2026
 
 
 
 
 
 
 
 Privacy Note:
 
 
 
 https://www.tcs.com/connect-with-tcs/privacy-policy
 
</div>

AI Engineer

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

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