{"id":34241,"url":"https://alion.io/job/razer-ai-software-engineer","title":"AI Software Engineer","company":{"id":3457,"name":"Razer","domain":"razer.com","url":"https://alion.io/company/razer","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":76,"open_postings":39,"ghost_share":0,"stale_share":0.949,"repost_share":0,"time_to_fill_p50_days":34,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":48000,"max_usd":123000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"Dask","optional":false},{"name":"Docker","optional":false},{"name":"Edge AI","optional":false},{"name":"GCP","optional":false},{"name":"gRPC","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LiteRT","optional":false},{"name":"Machine Learning","optional":false},{"name":"ONNX","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"TensorRT","optional":false},{"name":"Terraform","optional":false},{"name":"TFLite","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2025-04-22T00:00:00Z","employer_posted_date":"2025-04-22","last_verified_at":"2026-10-17T21:24:29Z","board_verified":true,"closed_at":null,"days_open":544,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":543},"description":"Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.\nJob Responsibilities :\nWe are seeking a highly skilled AI Software Engineer to design, develop, and deploy AI-powered solutions. This role involves building scalable AI systems, integrating AI / Machine Learning (ML) models into applications, and optimizing AI workflows for production. You will collaborate closely with data scientists, software engineers, and DevOps teams to bring cutting-edge AI capabilities to life.Implement and optimize AI / ML models in production, via containerization (Docker, Kubernetes), for speed, accuracy and cost-effectiveness\nDeploy AI models using RESTful APIs, gRPC, or edge computing solutions.\nImplement monitoring, logging, and error-handling mechanisms to track AI performance.\nDesign APIs and microservices to integrate AI capabilities into software systems to ensure that they are secure, performant and well-documented\nMonitor and optimize model performance in production environments, ensuring API latency and availability meet the required SLAs (Service Level Agreements).\nBuild scalable, high-performance AI pipelines for real-time and batch processing.\nImplement MLOps best practices, including CI/CD for machine learning workflows on both local machines and cloud platforms\nWork closely with data scientists to turn research models into deployable solutions.\nCollaborate with DevOps and cloud engineers to ensure seamless AI model deployment.\nStay up to date with the latest AI/ML frameworks, tools, and industry trends in API, plugins development to continuously improve and enhance API solutions.\nIdentify opportunities to improve existing AI API / plugins architectures and suggest new features or services to add value to AI products.\nPre-Requisites :\n3+ years of experience in AI/ML software development.\nProven track record of deploying AI solutions in production environments.\nStrong experience in deploying AI models and API development using RESTful APIs, gRPC, or edge computing solutions.\nStrong programming skills in Python, Java, or C++.\nHands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).\nIn depth understanding of containerization (Docker, Kubernetes) and DevOps practices.\nExperience in developing and deploying AI applications running both edge deployment (TensorRT, ONNX, TFLite) and on cloud infrastructure (AWS, Azure or Google Cloud Platform) using Infrastructure as code tools such as Terraform and also cloud AI services (AWS SageMaker, Google Vertex AI, Azure ML).\nExperience with database management (SQL, NoSQL, and vector databases).\nKnowledge of distributed computing (Spark, Dask) and parallel processing.\nAbility and willingness to learn any new technologies and apply them at work in order to stay ahead, in a fast paced, high pressure, agile environment\nExcellent written and verbal communication skills for coordinating across teams.\nEducation & Experience\nHas a Bachelor’s or Master’s degree in computer science, AI or similar discipline from an accredited institution\nTravel Requirements\nRole based in Singapore office and may require up to 1 travel trip per year.\nAre you 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