Machine Learning Engineer

rc Inventador is a fast-growing technology company specializing in building scalable and innovative SaaS solutions for global clients. We focus on software development, cloud-based product engineering, and digital transformation. Our team is passionate about delivering intelligent platforms that solve real-world business challenges across multiple industries.

As a Machine Learning Engineer, you will play a critical role in designing, developing, and deploying advanced NLP and conversational AI solutions. You will work on speech technologies, automation, and intelligent workflows, collaborating closely with backend engineers, product teams, and voice platform experts. This position requires strong technical expertise, hands-on coding skills, and a product-focused mindset.

Key ResponsibilitiesNLP Development

• Build and deploy NLP pipelines for intent detection, entity extraction, sentiment analysis, and conversational flow management using libraries such as NLTK, spaCy, or Transformers.
• Fine-tune and maintain language models to deliver domain-specific conversational experiences.

Machine Learning & Conversational AI

• Design and implement ML models for dialog management, FAQ automation, and multi-turn conversation flows across chat and voice platforms.
• Prototype intelligent automation features including call summarization, intent routing, and IVR automation.

Speech Technologies

• Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) systems (e.g., Whisper, Google STT/TTS, Amazon Polly).
• Monitor and optimize speech model performance, latency, and reliability in production.

Engineering & Deployment

• Develop scalable ML APIs and microservices for production-grade applications.
• Work with REST APIs for model integration and deployment.
• Collaborate with engineers and product managers to deliver production-ready ML solutions.

Data Handling & Research

• Process, annotate, and analyze large-scale multilingual datasets for training and validation.
• Document pipelines, workflows, and research findings to support knowledge sharing.

Required Skills & Experience

• Experience: 3–4 years in ML Engineering or NLP-focused roles.
• NLP Expertise: Hands-on experience with NLTK, spaCy, Transformers, or similar NLP frameworks.
• Machine Learning: Strong Python skills with PyTorch, TensorFlow, or scikit-learn.
• Speech Technologies: Experience developing STT/TTS solutions (Whisper, Google STT/TTS, Amazon Polly, etc.).
• APIs & Deployment: Proficiency in working with REST APIs, microservices, and ML model deployment.
• Version Control & Agile: Solid understanding of Git, Agile/Scrum workflows, and collaborative development.
• Coding Experience: Proven ability to write clean, maintainable, and scalable production code.
• Data Handling: Exposure to large text/audio datasets for model training and evaluation.

Job Type: Full-time

Work Location: In person