COMPANY OVERVIEW:

Lean Tech is a rapidly expanding organization situated in Medellín, Colombia. We pride
ourselves on possessing one of the most influential networks within software
development and IT services for the entertainment, financial, and logistics sectors. Our
corporate projections offer a multitude of opportunities for professionals to elevate their
careers and experience substantial growth. Joining our team means engaging with
expansive engineering teams across Latin America and the United States, contributing
to cutting-edge developments in multiple industries.
We are seeking a skilled Senior Machine Learning Engineer with expertise in Large
Language Models (LLMs) and audio processing to join our innovative team at Lean
Solutions Group. This role involves designing, developing, and deploying advanced
voice-based AI solutions to enhance customer experiences within our call center.
You will leverage your proficiency in speech recognition, Natural Language Processing
(NLP) technologies, and real-time streaming to create sophisticated voice bots that
automate interactions seamlessly. As a key contributor, you will integrate LLMs into
scalable, high-performance systems, work alongside cross-functional teams, and
constantly explore the latest machine learning advancements to ensure our solutions
remain cutting-edge. Embrace this opportunity to transform customer service through
AI-driven innovation.
Location: Remote

REQUIREMENTS & QUALIFICATIONS

To excel in this role, you should possess:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 4 years of experience as a Machine Learning Engineer or in a similar role.
• Advanced proficiency in Large Language Models (LLMs) for developing conversational AI and handling complex customer service requests.
• Expertise in audio processing and speech technologies, including ASR (Automatic Speech Recognition), TTS (Text-to-Speech), speech-to-text, and text-to-speech conversion.
• Intermediate proficiency in Python and relevant machine learning libraries such as TensorFlow, PyTorch, or Keras.
• Experience with audio processing libraries like librosa and Pydub, and tools such as Kaldi, DeepSpeech, or SpeechBrain.
• Advanced experience in Natural Language Processing (NLP) for tasks including intent recognition, entity extraction, and sentiment analysis.
• Familiarity with real-time streaming and latency optimization for voice communication.
• Experience with cloud platforms like AWS, Azure, or Google Cloud, particularly for speech processing services.
• Familiarity with call center technologies and customer service automation tools (preferred)
• Strong problem-solving skills and the ability to work in a fast-paced, team-oriented environment.
• Excellent communication skills for explaining complex technical topics to non-technical stakeholders.

SOFT SKILLS

• Exceptional problem-solving skills and an analytical mindset, crucial for developing and optimizing AI-driven solutions for customer service enhancements.
• Ability to thrive in a fast-paced, collaborative environment, working with cross-functional teams to deliver innovative voice-based AI solutions.
• Excellent communication skills, essential for translating complex technical concepts into accessible information for non-technical stakeholders.
• Strong leadership capabilities to guide project execution and mentor team members in advanced ML techniques and strategies.
• Dedication to enhancing customer experiences through AI and automation, reflecting a passion for pioneering advancements in machine learning and voice technologies.

WHAT YOU WILL BE DOING:

• Design and deploy advanced voice bots using Large Language Models (LLMs) to handle customer queries in real-time during voice calls, enhancing customer interactions.
• Develop and optimize ML models for real-time audio and speech analysis, focusing on speech recognition, speaker identification, and sentiment analysis to improve accuracy and effectiveness.
• Apply audio signal processing techniques to enhance voice quality, including noise cancellation, speech enhancement, and voice activity detection to ensure clarity in conversations.
• Collaborate with cross-functional teams, including product managers and data scientists, to define technical requirements and improve model performance through real-world feedback.
• Continuously monitor and optimize voice bot performance, implementing real-time feedback mechanisms to maintain high customer satisfaction and accurate response rates.
• Stay informed about the latest advancements in machine learning, LLMs, and voice technology, ensuring the integration of cutting-edge solutions into our AI systems.

To excel in this role, you should possess:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 4 years of experience as a Machine Learning Engineer or in a similar role.
• Advanced proficiency in Large Language Models (LLMs) for developing conversational AI and handling complex customer service requests.
• Expertise in audio processing and speech technologies, including ASR (Automatic Speech Recognition), TTS (Text-to-Speech), speech-to-text, and text-to-speech conversion.
• Intermediate proficiency in Python and relevant machine learning libraries such as TensorFlow, PyTorch, or Keras.
• Experience with audio processing libraries like librosa and Pydub, and tools such as Kaldi, DeepSpeech, or SpeechBrain.
• Advanced experience in Natural Language Processing (NLP) for tasks including intent recognition, entity extraction, and sentiment analysis.
• Familiarity with real-time streaming and latency optimization for voice communication.
• Experience with cloud platforms like AWS, Azure, or Google Cloud, particularly for speech processing services.
• Familiarity with call center technologies and customer service automation tools (preferred)
• Strong problem-solving skills and the ability to work in a fast-paced, team-oriented environment.
• Excellent communication skills for explaining complex technical topics to non-technical stakeholders