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Fullstack engineer at OCBC Bank in Singapore building and maintaining scalable banking applications and services: RESTful APIs, user interfaces, and automation across Windows, macOS, and Linux servers. Core stack: Java plus C#/Kotlin/Golang, microservices, Kubernetes/Docker, and React/AngularJS front ends.
Platform engineer on OCBC's enterprise data team, administering the bank's Data, Analytics and AI/ML platforms — Cloudera CDP/CML, Hadoop and Spark across hybrid AWS and on-premises infrastructure, plus Kubernetes/OpenShift and AWS AI services. Day to day: platform upgrades, security patching, monitoring, troubleshooting, and automation with Python/Shell.
Committed Staff (an outstaffing firm placing LATAM engineers with U.S. companies) is hiring a Cloud Infrastructure & DevOps Engineer to own the AWS environment of a GPS technology client, fully remote. Day to day: managing Terraform-based AWS infrastructure, driving cost optimization, building CI/CD pipelines (GitHub Actions), Docker/ECS, security (IAM, WAF), and CloudWatch monitoring.
Java Developer (up to £55k) at a global technology consultancy, building modern cloud-based microservices platforms for secure, large-scale digital transformation programmes across multiple industries. Day to day: backend Java development alongside senior engineers on a growing team.
Full-stack engineer at Tracium GmbH building an AI-assisted technical documentation authoring platform (S1000D, initially maritime). Day to day you build a React/TypeScript editing UI, backend APIs in Python or Node.js, and integrate AI/document-processing services, plus validation, versioning, access controls, and export workflows. Early-stage startup in Hamburg, remote-friendly.
Senior Data Engineer at Tracium (Berlin) will build the data foundation for its AI-assisted technical documentation product: designing document ingestion/processing pipelines for PDFs and XML, defining data models, and ensuring traceability, resilience, and reproducible processing. Core stack: Python, SQL, workflow orchestration, cloud, containers, and infrastructure as code.
Senior AI Engineer at Tracium (Berlin) owns the AI capabilities of a document-intelligence platform for technical documentation: building parsing/OCR/layout pipelines, LLM-based retrieval and structured extraction workflows, and evaluation of accuracy across cloud and private deployments. Core stack is Python, LLMs, and document processing.
Data Engineer at Penlink (Lincoln, NE) builds and maintains the data pipelines and infrastructure that power AI and analytics in the company's law-enforcement investigative software. Day to day: ETL/ELT development, SQL and data modeling, cloud/distributed data systems, and secure handling of sensitive telecom and digital-evidence data.
Lead Machine Learning Engineer at Faculty (London) driving technical direction and delivery of complex ML and software projects for the company's Life Sciences team, serving pharma and MedTech clients. Involves architecting scalable ML systems, mentoring engineers, and advising stakeholders, using Python plus a typed language, a major cloud (Azure/GCP/AWS), Docker, and Kubernetes.
Lead development of speech-recognition (ASR) systems for automated children's reading assessment across multiple languages at Pratham's PraDigi initiative — owning speech data collection/annotation, model training and fine-tuning (Whisper, wav2vec 2.0, Conformer, CTC/RNN-T), error analysis, benchmarking, and deployment for low-bandwidth/offline settings, using Python and PyTorch with toolkits like
Builds and maintains SemiAnalysis's client-facing dashboards (TCO, Tokenomics, CCM) that present the firm's AI infrastructure and GPU economics models, working directly with analysts to load model data, validate inputs, and ensure numerical accuracy. Core stack: Python or TypeScript, with React/Next.js preferred, and daily use of AI coding agents.
Security-focused SRE on InfraCloud's security team, deploying and managing security tooling across large multi-region Kubernetes clusters (cloud and on-prem). Day to day: build DevSecOps pipelines for SDLC, SBOM, SIEM and runtime security, automate compliance and CVE tracking, and handle incident response and forensics with tools like Wazuh, Trivy, Falco and DefectDojo.
Software developer at Krishagni, a Pune-based product company building OpenSpecimen, a biospecimen management platform for clinical research used by hospitals and universities worldwide. Day to day involves strong programming, Java (Spring, Hibernate), AngularJS, REST APIs, and deep database/SQL work including transactions and performance engineering.
Embedded AI engineer at ScaleOps working with the go-to-market org (sales, SEs, CS, marketing) to map workflows and ship AI agents and automations on the internal platform with connectors like Salesforce, Gong, Slack, and Google Workspace. Day to day: scoping solutions, writing prompts/skills/evals, iterating with users, and driving adoption during US hours.
Senior engineer on Init's AI Enablement team designing, building, and scaling internal LLM-based solutions from POC to production — integrating Azure AI Foundry, open-source LLM orchestrators, and self-hosted frontends, with RAG, prompt engineering, data pipelines, and mentoring of an AI Developer.
Database engineer at M2 Technology Group supporting critical national-security solutions at Fort Meade: designing and tuning MongoDB deployments, automating security monitoring, building data parsers/loaders, and developing Python microservices with Django/Flask. Requires an active NSA TS/SCI clearance with polygraph; salary $180k–$230k.
An AI Developer joins Init's AI Enablement team to build AI-powered features and integrations, support POCs, and help maintain AI infrastructure (Azure AI services, open-source LLM orchestrators, self-hosted LLM frontends) under guidance from senior engineers. Core stack: Python, LangChain/Hugging Face, LLMs, Git, and Azure.
Remote, project-based (outstaff) Middle+/Senior Python/AI engineer building an MVP service that ingests financial documents (Excel, PDF, scans), extracts and normalizes data, and reconciles records to surface discrepancies. Core stack: Python, FastAPI, pandas, REST, Docker, PostgreSQL, plus OCR/Document AI and optional LLM API integration.
QA automation engineer designing and executing manual and automated tests for Python-based applications and services: writing test cases/plans and regression suites, testing APIs and web apps, documenting defects, and reporting risks to stakeholders. Core stack: Python with Pytest, SQL, REST APIs, and Git.
A hands-on senior C++ engineer role building and optimizing low-latency, real-time trading infrastructure for a proprietary trading firm: designing high-performance components, profiling and tuning systems, and mentoring other engineers. Core stack is modern C++ with networking (TCP/UDP/WebSockets), message queues like ZeroMQ/Kafka, and optional Python/Rust.
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