unifyCX - Staff Artificial Intelligence/Machine Learning Engineer (10-15 yrs)

Title of the Position : Staff AI/ML Engineer- Tech Lead

Designation : Staff AI/ML Engineer- Tech Lead

Work Location : Remote

Business Unit : Engineering

Shifts: General (candidate should be flexible)

Who We Are :

unifyCX is an emerging Global Business Process Outsourcing company with a strong presence in the U.S., Colombia, Dominican Republic, India, Jamaica, Honduras, and the Philippines. We provide personalized contact centers, business processing, and technology outsourcing solutions to clients worldwide. In nearly two decades, unifyCX has grown from a small team to a global organization with staff members all over the world dedicated to supporting our international clientele.

At unifyCX, we leverage advanced AI technologies to elevate the customer experience (CX) and drive operational efficiency for our clients. Our commitment to innovation positions us as a trusted partner, enabling businesses across industries to meet the evolving demands of a global market with agility and precision. unifyCX is a certified minority-owned business and an EOE employer who welcomes diversity.

Overview :

The AI Engineering team at UnifyCX is looking for a motivated, challenge driven full stack Staff AI/ML Engineer specializing in Language Models to join us in building our next-gen omnichannel CX delivery and process automation platform Lightbird.

We are a pioneering company at the intersection of technology and human-centric services, delivering innovative AI solutions that empower businesses to transform customer experience at scale.

Embrace the challenge of architecting, designing, and optimizing production-grade ML solutions that push the boundaries of AI-human interaction. As a Staff AI/ML Engineer, you will not only craft robust, domain-aware models and human-aligned AI copilots across text and audio but also provide the technical leadership and vision to guide critical projects, mentor team members, and ensure strategic alignment across the organization.

Roles and Responsibilities :

Model Development :

- Design, train, and optimize cutting-edge domain-aware ML models, leveraging both classical ML and deep learning architectures.

- Incorporate multi-modal approaches (text, voice, context) to deliver robust and guardrailed AI copilots capable of nuanced human interaction.

- Tackle challenging modeling issueslike handling sparse data, multi-turn dialogues, or domain adaptationby leveraging a deep understanding of AI fundamentals.

Develop Scalable Solutions :

- Build, deploy, and maintain robust ML pipelines (data ingestion, feature engineering, model training, model serving) that perform reliably in high-traffic production environments.

- Proactively identify bottlenecks in data processing or inference, and implement optimizations or architectural changes to meet stringent latency and throughput requirements.

- Establish metrics and monitoring practiceslatency, accuracy, model driftto ensure solutions remain performant and stable post-deployment.

Research & Innovation :

- Stay current with leading AI/ML research, driving proof-of-concepts for new solutions.

- Experiment with emerging algorithms, sharing learnings through talks and white papers.

- Translate novel approaches into tangible, impactful product features.

- Embrace emerging AI trends and champion ethical, responsible development for transformative impact.

Thrive in Agile Environments :

- Work cross-functionally with data scientists, software engineers, and product managers to drive new AI-powered product initiatives.

- Engage in sprints, code reviews, and iterative development to maintain quality and accelerate delivery. Maintain clear, comprehensive documentation and uphold strong engineering standards.

Technical Leadership & Mentorship :

- Encourage diverse perspectives to drive innovation and excellence.

- Own architectural decisions to ensure maintainable, scalable solutions.

- Lead critical AI/ML initiatives, aligning cross team technical stakeholders to agile, high velocity solutions that serve broader business goals.

- Mentor junior team members, providing guidance on complex algorithmic challenges, code reviews, and best practices. Communicate technical details to non-technical stakeholders for informed decisions.

Qualifications :

Required :

- Masters degree in Computer Science, Electrical Engineering, Applied Math, Physics, or a related field.

- 7+ years post Masters / 4+ years post Ph.D. / 10+ years industry experience or equivalent in practical machine learning engineering with demonstrated mastery in designing and deploying models for language/ audio/image/ time series tasks.

Technical Skills :

- Expert-level proficiency in Python and hands-on experience building solutions in PyTorch or TensorFlow, including custom model architectures and performance optimization.

- In-depth understanding of Transformer architectures, RNNs, text embedding techniques, and large-scale language/speech applications, including guided generation and alignment.

- Experience implementing privacy-preserving techniques and robust guardrails (bias detection, content filtering), ensuring ethical AI development and safe inference at scale.

- Background deploying and maintaining production ML models on AWS, GCP, or Azure, including containerization, CI/CD pipelines, and monitoring solutions.

- Familiarity with version control of ML models, including tracking datasets, hyperparameters, and metrics through tools like MLflow or Weights & Biases. Ability to ensure reproducible training runs, effective model governance, and robust experiment tracking.

Production Software Engineering : Ability to design, build, test, and maintain customer-facing software with strong knowledge of version control (Git) and project management tools (JIRA/Asana).

Team Leadership :

- Demonstrated track record leading complex AI projects or initiatives, mentoring junior engineers, and setting technical standards.

- Capable of translating complex ML concepts into actionable plans for diverse stakeholders, from executives to product teams.

- Experience fostering a culture of learning and continuous improvement, building cross-functional relationships.

- Adept at diagnosing and resolving intricate ML and systems-level challenges under time constraints.

Preferred :

- Advanced Degree : Ph.D. in Computer Science, Machine Learning, or related fields.

- Regulated Industries: Industry experience in high-compliance sectors (e.g., healthcare, finance, cybersecurity), including custom ML model development and familiarity with the unique challenges of regulated environments is highly preferred!

- Project Management : Experience orchestrating sprints, backlog tracking, and cross-team coordination using JIRA or similar too

- AI Guardrails : Background in designing robust ethical guardrails (e.g., bias detection, content filtering) for responsible AI deployment. Experience with guided generation and model alignment, and privacy preserving safe AI techniques in training and inference.

- Open Source & Publications : Contributions to open-source AI projects or notable academic publicationsdemonstrating thought leadership in the AI community.

- Distributed Systems : Experience scaling ML workloads via distributed architectures or large-scale model serving.

- Real-Time Processing : Familiarity with real-time audio processing, streaming technologies, and low-latency model inference