Joan G.-Senior Software Engineer
Check rate
Experience
Senior Software Engineer
Pildo Labs
- Architected and developed scalable Java and Python backend services, integrating real-time data from multiple systems into centralized monitoring and decision-support platforms used by engineering teams.
- Owned end-to-end integration of data-processing and monitoring services, improving operational workflows and reducing manual anomaly-review effort by approximately 25%.
- Designed Python-based AI and machine-learning components using PyTorch to analyze high-volume operational data, identify abnormal patterns, and support data-driven engineering decisions.
- Built AI-assisted decision-support prototypes and translated machine-learning outputs into production-oriented workflows, working with research and engineering teams to validate practical use cases.
- Led a cross-functional engineering team through system design, implementation, integration, and troubleshooting, coordinating work across software, data, telecommunications, and research teams to deliver project milestones on schedule.
- Developed backend and automation capabilities for VITAS, a two-year €2.9M EU-funded R&D program, contributing to digital-twin, monitoring, and operational-validation solutions across multiple industry partners.
- Led architecture reviews, technical debugging, and root-cause analysis across distributed services, helping resolve complex integration and data-quality issues before major validation and release milestones.
Machine Learning Engineer
Red Points
- Built Python backend and ML services for a brand-protection platform that supports large-scale automated infringement detection and enforcement across global online marketplaces for enterprise brand customers.
- Built multimodal NLP and computer-vision pipelines that process over 35 million new marketplace links daily, combining text embeddings, imagery, and product metadata to prioritize automated enforcement.
- Designed scalable training workflows for highly imbalanced datasets using hard-negative mining, class weighting, and threshold optimization to improve precision and reduce false positives across models.
- Established evaluation pipelines using precision, recall, F1, PR-AUC, and confusion matrices, turning high-volume operational results into repeatable model-validation and continuous improvement cycles for the team.
- Built containerized inference services with FastAPI, PyTorch, Docker, and AWS, implementing model versioning, automated testing, production monitoring, and rollback mechanisms for reliable enforcement platform deployments.
- Led technical reviews across ML, backend, and data-engineering initiatives supporting a platform responsible for hundreds of thousands of enforcement notices each month and significant customer revenue protection.
Software Engineer
Happy Scribe
- Built core backend services as Happy Scribe grew from an early user base to over one million users, processing more than sixty years of cumulative audio and video content.
- Designed asynchronous media-processing pipelines for long-running transcription workloads, improving job orchestration, failure recovery, and background processing as platform demand and content volume grew significantly each quarter.
- Integrated speech-recognition APIs into workflows that could process one hour of speech in roughly twenty minutes, generating timestamped data for synchronized transcription and subtitle editing.
- Improved scalability by optimizing REST endpoints, database queries, and asynchronous workers, removing backend bottlenecks as transcription volume and international usage grew rapidly across new global markets.
- Delivered production features for transcript editing, synchronized playback, subtitle generation, exports, authentication, and payments for Happy Scribe's rapidly growing international SaaS transcription platform used by customers worldwide.
Industry experience
See where this freelancer has spent most of their professional time.
Experienced in Information Technology and Aerospace and Defense.
Business area experience
See which departments and functions this freelancer has contributed to most.
Experienced in Information Technology, Product Development, and Project Management.
Summary
Senior Software Engineer with 8+ years of experience architecting mission-critical systems at scale. Technical leader driving architecture and design across production ML platforms (35M+ links/day infringement detection, 4.6M+ enforcements/year), high-volume SaaS infrastructure (1M+ users, 60+ years of cumulative media processed), and aerospace software (€2.9M EU program, real-flight validation in progress). Expertise in distributed systems, production ML, Python/Java backends, PyTorch/TensorFlow pipelines, AWS cloud architecture, and reliability engineering. Proven ability to own technical direction for complex initiatives, bridge research and production needs, and turn requirements into resilient, observable systems.
Skills
- System Design & Architecture: Distributed Systems, Microservices, Event-Driven Architecture (Kafka/Flink), Api Design, Asynchronous Processing, High-Throughput Data Pipelines, Reliability Engineering, Performance Optimization, Fault Tolerance
- Backend Engineering & Languages: Python 3.8+, Java 11+, Rest/Grpc Apis, Sql, Fastapi, Flask, Service-Oriented Architecture, Background Workers, High-Volume Data Processing, Connection Pooling, Query Optimization
- Machine Learning & Ai: Pytorch (Inference Optimization, Model Serving), Tensorflow, Scikit-Learn, Rapids; Nlp (Text Embeddings, Classification, Ranking), Computer Vision, Multimodal Models, Imbalanced Classification (Hard-Negative Mining, Class Weighting, Focal Loss), Feature Engineering, Model Evaluation (Precision-Recall, F1, Confusion Matrices), Shap Explainability
- Cloud & Production Operations: Aws (Lambda, Sagemaker, S3, Rds, Ec2, Cloudwatch), Docker, Kubernetes, Ci/Cd (Github Actions, Gitlab Ci), Containerized Services, Structured Logging (Elk, Cloudwatch), Distributed Tracing, Production Debugging, Incident Analysis, Observability
- Databases & Data Engineering: Postgresql, Mysql, Redis, Data Modeling, Etl Pipelines, Data Quality Validation, Large-Scale Data Processing, Caching Strategies, Connection Management
- Testing & Reliability: Automated Testing (Unit, Integration), Failure Recovery, Chaos Engineering, Root-Cause Analysis, Performance Profiling, Production Troubleshooting, Cross-Functional Collaboration
Languages
Education
Universitat de Barcelona
Master's Degree · Advanced Mathematics · Barcelona, Spain
Universitat Pompeu Fabra
Bachelor's Degree · Computer Engineering · Barcelona, Spain
Statistics
Experience
Global experience
Expertise
Qualifications
Frequently asked questions
Have questions? Find more information here.
Joan is based in Tarragona, Spain.
Joan speaks the following languages: Spanish (Native), English (Advanced).
Joan has at least 9 years of experience. During this time, Joan has worked in at least 3 different roles and for 3 different companies. The average length of individual experience is 3 years and 11 months. Note that Joan may not have shared all experience and actually has more experience.
Based on recent experience, Joan would be well-suited for roles such as: Senior Software Engineer, Machine Learning Engineer, Software Engineer.
Joan's most recent position is Senior Software Engineer at Pildo Labs.
In recent years, Joan has worked for Pildo Labs and Red Points.
Joan is most experienced in industries like Information Technology and Aerospace and Defense.
Joan is most experienced in business areas like Information Technology, Product Development, and Project Management.
Joan has recently worked in industries like Information Technology and Aerospace and Defense.
Joan has recently worked in business areas like Information Technology, Product Development, and Project Management.
Joan holds a Master in Advanced Mathematics from Universitat de Barcelona and a Bachelor in Computer Engineering from Universitat Pompeu Fabra.
The availability of Joan needs to be confirmed.
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Calculated based on our freelancers’ daily rates as of 6 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
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