ML Engineer

What we're looking for

We are seeking an experienced engineer who sits at the intersection of machine learning, data engineering, and cloud-native infrastructure. The ideal candidate has a proven track record of designing, deploying, and scaling ML systems in production using Kubernetes and microservices, and can work self-sufficiently with limited oversight. This is a highly collaborative role: while you will have autonomy in day-to-day execution, you will meet regularly with the management team to align on priorities, define success for upcoming deliverables, and shape technical strategy.

Key Responsibilities:

-Architect, build, and maintain scalable ML pipelines and data workflows using Kubernetes-based microservices;

-Deploy, monitor, and optimize ML inference services for reliability, cost efficiency, and low latency;

-Collaborate with data scientists and ML researchers to productionize and optimize models for performance and scale;

-Design and implement data ingestion, transformation, and storage solutions to support training and inference workloads;

-Own end-to-end system performance: profiling, debugging, and implementing optimizations;

-Contribute to long-term infrastructure strategy, ensuring our platform is robust, modular, and future-proof;

-Work independently while providing clear communication, updates, and progress tracking to management.

Profile and Requirements:

-4-8 years of professional experience spanning software engineering, data engineering, and ML engineering;

-Deep expertise in Kubernetes, Docker, and microservices architectures;

-Strong background in data engineering: pipelines, distributed data systems, ETL, and storage technologies (SQL/NoSQL, data lakes, etc.);

-Hands-on experience with ML model deployment (e.g., TensorFlow Serving, TorchServe,Triton Inference Server, custom APIs);

-Proven ability to optimize ML models (quantization, pruning, batching, caching strategies);

-Proficiency with Python as a primary language;

-Excellent communication skills, with ability to work self-directed and translate high-level objectives into actionable plans.

Nice to Have:

-Experience with GPU/accelerator-based inference optimization;

-Familiarity with vector databases, embeddings, and large-scale search systems;

-Knowledge of streaming data platforms (Kafka, Pulsar, etc.);

-Ability to work in JavaScript/TypeScript for API or front-end integrations;

-Prior experience in a startup or fast-moving environment.

What we can offer

At Optimizer, we prioritise your well-being and growth with a benefits package that includes:

-Home Office Flexibility;

-Health Insurance;

-Up to 25 Days of Annual Vacation;

-Meal Allowance;

-Laptop, Mobile Phone, and Mobile Data Plan;

-Employee Referral Rewards;

-Exclusive Partnerships;

-Learning & Development Programmes;

-Career Growth Opportunities;

-Gym Membership or Sports Subscription;

-Annual Performance Bonus

To apply:

Send us your CV to recrutamento@optimizer.pt

www.optimizer.pt

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Contacts and address

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Praça Dr Francisco Sá Carneiro Nº 219 2º esq. 4200-313 Porto