AI/ML Engineer
2 semanas atrás
Company Description We take a multidisciplinary approach that combines technology consulting, AI implementation, and the development of scalable SaaS solutions. Our mission is to help businesses modernize their operations, unlock growth, and achieve digital transformation through practical, measurable innovation. Our team unites experts in software engineering, data science and machine learning from companies such as Google DeepMind , Microsoft , US Army Corps of Engineers and Salesforce . Role Description This is a full-time role for a AI/ML Engineer. As an AI/ML Engineer you will be responsible for developing, training and maintaining machine learning systems, integrating with LLM APIs and keeping the infrastructure for running models. This is a fully remote role where you expected to meet with the team during the central european timezone. What you’ll love about this role High ownership over features and architecture from day one. Tight product/design/engineering collaboration; your work ships weekly. Clear 30/60/90‑day impact plan and hands‑on mentorship. Impact you’ll own in the first 30 days Benchmark: Evaluate and decide the best technical approach for a key customer-facing problem. NLP Solution: Train a classical ML model to solve a core text processing task. Ship Features: Deploy two ML features end-to-end with measurable customer impact. Strengthen Infra: Improve cloud infrastructure and service reliability. Enable the Team: Upgrade the developer experience via better docs, CI, or tooling. What you’ll do Design and implement scalable machine learning models. Build and manage robust data processing pipelines. Perform model training, validation, and hyperparameter tuning. Evaluate model performance and ensure high accuracy. Drive innovation in the GenAI space to build customer solutions. Collaborate with software teams for model deployments. Stack you’ll touch Frameworks: PyTorch, NumPy, SciPy, NLTK and spaCy. Backend: Python with FastAPI. LLM APIs: OpenAI Data: PostgreSQL (or similar relational DB). Cloud: AWS / GCP, Docker, Kubernetes and Terraform. What you bring Master's degree in Computer Science, Statistics, or a related quantitative field. Minimum 1 year of professional experience as an ML Engineer or Data Scientist. Expert-level proficiency in Python and its ML ecosystem. Deep practical experience with major frameworks like PyTorch or TensorFlow. Strong background in statistical analysis and model evaluation. Practical knowledge of GenAI systems (LLMs) and implementations (RAGs). Ability to write clean, maintainable, and well-documented research code. Nice to have Over 2 years working as a Machine Learning Engineer or Data Scientist. Demonstrated experience with distributed machine learning (e.g., Spark, Dask). Practical experience using LLM APIs (such as OpenAI) to develop RAG systems. Familiarity with containerization tools (Kubernetes and Docker). Domain expertise in NLP, Computer Vision, or Reinforcement Learning. How we work Fully remote with office in Porto; async‑friendly practices; frequent releases. Pragmatic testing and CI; code reviews as a learning loop. Competitive salary with meaningful responsibility from day one. Transparent ranges early in process; mentorship + learning time. Job details Seniority level: Junior–Mid (1–3 years) Employment type: Full‑time Workplace type: Remote Job functions: Machine Learning, Software Engineering, Information Technology, Data Science Industries: Software Development, IT Services & Consulting, Artificial Intelligence
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