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Mid/Senior AI Engineer

Role overview

Qualifications

  • 2+ years of professional experience in Machine Learning, AI Engineering, or a related role
  • Proven experience building and deploying ML models in production environments
  • Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
  • Master’s degree in AI, Machine Learning, Computer Science, or a related field is a strong plus

Responsibilities

  • Take ownership of key components within ML and GenAI projects
  • Contribute to architectural and technical decisions in a collaborative environment
  • Build scalable ML systems that move from experimentation to real-world application
  • Support and mentor junior team members

Key facts

  • Remote from: Portugal
  • Full time
  • Senior (5-10 years)
  • AI Engineer
  • English

Hard skills

Other skills

  • Collaboration
  • Mentorship
  • Communication

About the company

TensorOps logo

TensorOps

Artificial Intelligence & Machine Learning Services

TensorOps is a leading provider of machine learning (ML) and artificial intelligence (AI) services for startups and companies. The company specializes in two key areas: Search Relevance and TimeSeries. Search Relevance: TensorOps helps companies improve their search algorithms to deliver more relevant results to their customers. This involves analyzing search queries, optimizing ranking algorithms, and developing custom solutions to improve search relevance. By improving search relevance, companies can increase customer engagement, retention, and ultimately revenue. TimeSeries: TensorOps provides expertise in TimeSeries forecasting, which is a technique used to predict future values based on historical data. This is particularly useful for companies that deal with time-sensitive data, such as financial data, healthcare data, and manufacturing data. TensorOps works with companies to develop custom forecasting models that can help them make more accurate predictions, improve planning, and optimize resource allocation. TensorOps is known for its high level of expertise, customer service, and attention to detail. The company works closely with clients to understand their needs and develop tailored solutions that deliver tangible business results. Whether it's improving search relevance, optimizing forecasting models, or developing custom ML and AI solutions, TensorOps is committed to helping its clients succeed in today's fast-paced business environment.

Company details

IndustryArtificial Intelligence & Machine Learning Services
Company size2 - 10

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Job description

We are building a pipeline of talented Machine Learning Engineers for upcoming projects at TensorOps. While we may not have an immediate opening, we are continuously growing and would love to connect with strong candidates for future opportunities.

If you are passionate about ML systems, GenAI, and production-grade deployments, we’d love to hear from you.

About the role

We’re looking for Machine Learning Engineers who enjoy building practical, production-ready AI systems and collaborating on meaningful projects.

In this role, you will:

  • Take ownership of key components within ML and GenAI projects, with support from senior team members when needed

  • Contribute to architectural and technical decisions in a collaborative environment

  • Build scalable ML systems that move from experimentation to real-world application

  • Work with international clients to understand requirements and implement thoughtful technical solutions

  • Support and mentor junior team members as you grow in your own leadership journey

You’ll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning. 

Technical Expertise

We’re looking for engineers with strong hands-on experience across:

  • Python: Writing clean, efficient, well-documented, production-quality code

  • Machine Learning Frameworks: Designing, training, optimizing, and deploying models independently (e.g., PyTorch, TensorFlow, Scikit-learn)

  • GenAI & LLM Systems: Building RAG pipelines, chatbot architectures, and applications using tools like LangChain

  • MLOps & Production ML: Model versioning, monitoring, CI/CD for ML workflows

  • Cloud Deployments: Deploying and scaling ML systems on AWS, GCP, or Azure

  • Performance Optimization & Debugging: Diagnosing complex issues and improving system reliability and efficiency

Requirements 

  • 2+ years of professional experience in Machine Learning, AI Engineering, or a related role
  • Proven experience building and deploying ML models in production environments
  • Experience working with stakeholders or clients is a plus
  • Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
  • Master’s degree in AI, Machine Learning, Computer Science, or a related field is a strong plus
  • Equivalent practical experience building and deploying production ML systems will also be considered

What We Offer

  • 100% Remote Work: Work from anywhere with flexibility and autonomy
  • Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
  • International Clients: Collaborate with global organizations and solve real-world challenges at scale
  • Urban Sports Club Membership: Supporting your physical and mental wellbeing
  • Monthly Bolt Credits: For rides
  • Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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