Machine Learning Engineer

Arc Inventador is a fast-growing technology company focused on building scalable and innovative SaaS (Software as a Service) solutions for global clients. We specialize in software development, cloud-based product engineering, and end-to-end digital transformation. Our team is passionate about delivering high-performance platforms that solve real-world business challenges across multiple industries.

The ML Engineer will be responsible for designing, developing, and deploying machine learning solutions focused on Natural Language Processing (NLP), conversational AI, and speech technologies. You will drive innovation in automation and intelligent workflows, collaborating closely with backend engineers, product teams, and voice platform specialists. This role demands both deep technical expertise in ML/NLP and a practical, product-centric mindset.

Key Responsibilities

• Develop and deploy NLP pipelines for intent detection, entity extraction, sentiment analysis, and conversational flow management using NLTK, spaCy, or similar libraries.
• Design and implement machine learning models to automate dialog management, FAQ handling, and multi-turn conversation flows for voice and chat channels.
• Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) technologies (e.g., Whisper, Google STT/TTS, Amazon Polly).
• Fine-tune and maintain language models for industry-specific conversational experiences.
• Collaborate with software engineers and product owners to build scalable, production-ready ML APIs and microservices.
• Analyze large, multilingual datasets and annotate data to train, validate, and optimize ML models.
• Monitor and optimize model performance, latency, and reliability in production.
• Prototype and implement intelligent automation features (e.g., call summarization, intent routing, IVR automation).
• Document research findings, pipelines, and contribute to knowledge sharing within the team.
• Stay abreast of the latest advancements in conversational AI, NLP, and speech processing.

Required Skills & Experience

• 3–4 years of professional experience in ML Engineering or NLP-focused Data Science roles.
• Proven hands-on experience with NLTK (and/or spaCy, Transformers) for NLP pipeline development.
• Strong Python programming skills: familiarity with libraries such as scikit-learn, PyTorch, or TensorFlow.
• Experience developing, deploying, and maintaining STT/TTS solutions for production (Whisper, Google STT/TTS, Amazon Polly, or similar).
• Solid understanding of conversational AI, dialog management, and automation for contact center or voice platforms.
• Experience working with REST APIs, microservices, and deploying ML models as web services.
• Exposure to handling, processing, and annotating large-scale text/audio datasets.
• Familiarity with Agile development, version control (Git), and collaborative workflows.

Job Type: Full-time

Work Location: In person