AI Software Engineer

Do you feel like you’re just coding toy problems without making a real impact? Join us for a fulfilling career as a Software Engineer specializing in Big Data Pipelines and ML Automation, where you’ll tackle concretely defined, real-world challenges. At Imnoo, you’ll make a significant impact on automating manufacturing processes through robustbig data engineering, scalabledata pipelines, andmachine learning integrations, gaining invaluable experience inPython development,C# programming,C++ expertise, and deep satisfaction along the way We’re looking for an experienced Software Engineer - Big Data / Pipelines with an ML Flavourwho is passionate aboutautomation,AI/ML engineering, and ready to build scalableETL pipelines, process massive datasets, and infusemachine learning modelsinto production systems using strongPython coding skills,C# development, andC++ performance optimization. Why Join Us? | Career in Big Data Engineering & ML A clear path for career growth in machine learning engineering and data engineering roles. The opportunity to solve real and meaningful challenges in data-intensive manufacturing automation,computer vision, and AI-driven pipelines. A dynamic and flexible work environment supporting remote software development. Opportunities for professional development,certification support in AWS, Azure, andMLOps. A platform to share your ideas and opinions, where they are highly valued in our startup tech team. Your Playground | Hands-On Big Data & ML Projects Work on real/hands-on problems involvingbig data processing andautomation toolsforindustrial AI. Develop efficientdata pipelinesand tools that directly impact the day-to-day operations of our manufacturers Design and implement advanceddata extraction,feature engineering, processing, andpipeline orchestrationsolutions for handling CAD, 2D, 3D, and large‑scale batch data (filtered/unfiltered) with a focus onML applicationslikedeep learning modelsandpredictive analytics. Engineer scalablebig data infrastructure,cloud‑native services,RESTful APIs, automatedML model training and deployment, andCI/CD build toolsusingDockerandKubernetes. Own services end‑to‑end, from proof of concept to production‑ready solutions in high‑load environments withscalability testingandperformance tuning. Gain in‑depth knowledge of interconnectedcloud computing,big data ecosystems(Hadoop, Spark),computer vision pipelines, andML frameworksacrossPython,C#,C++, and multiple platforms likeLinux/Unix systems. Maintain and enhanceoptimization algorithms,machine learning services, andneural network integrationswithin data pipelines. Improve 2D/3D/CAD tools and solutions through automated, data‑driven workflows, includinggeometric modeling,simulation tools, andGPU accelerationwith CUDA. (Middlemen such as recruiting agencies are not welcome and will be automatically disqualified) Best to Have: | Essential Skills for Big Data ML Engineer Roles Strong software / coding skills inPython development,C# .NET programming, andC++ expertisewith a passion formachine learning,deep learning, andprocess automation. 5+ years of experience in dynamically typed (e.g.,Python scripting) and statically typed languages (e.g.,C# backend,C++ systems programming). Strong problem‑solving skills for building efficient, scalabledata pipelinesandML workflowsunder production constraints. Foundations or experience in 3D/geometry processing,game development engines(Unity/Unreal), fluid simulations,real‑time rendering,CUDA GPU programming, or similar technologies to handle complexbig data analyticsandspatial data. Nice to Have: | Preferred Qualifications for ML Pipeline Developers Educational background in mathematics, statistics, orcomputer sciencewith strong dedication and experience in applied technologies likeapplied MLanddata science(nice to have). CAD data processingexperience, including STEP/IGES formats (nice to have). Industry/Mechanical experience inCNC machining,robotics automation, and related fields (optional). Hands‑on experience inFrontend development(e.g., Angular, React) andBackend engineering(Node.js, .NET) (optional). Full‑stack developmentexperience withmicroservices architecture(optional). Familiarity with popularmachine learning librariesanddeep learning frameworks, such as scikit‑learn,PyTorch,TensorFlow, andPyTorch Lightning(nice to have). Experience withML model industrializationtools, includingmodel quantization,ONNX export,Docker containerization, andserverless deployment(nice to have). Knowledge ofMLOps practices,ML pipeline development, and tools like MLflow or Kubeflow (nice to have). Expertise inbig data processing,data clustering,anomaly detection, filtering, indexing, and querying large datasets efficiently usingElasticsearchorBigQuery(nice to have). Proficiency in automatedmodel training pipelinesandA/B testing deployment(optional). Strategicdata analysisand research skills, includingstatistical modeling,error propagation analysis, and identifying clusters or outliers inhigh-dimensional data(optional). Experience withcloud platforms, particularlyAWS services(S3, Lambda, SageMaker) andAzure Cloud Services(Data Factory, ML Studio) (optional). Strongdatabase skills: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra) fordata warehousing(optional). Deep understanding ofadvanced data structuresand algorithms forefficient querying(optional). #J-18808-Ljbffr