About the Company
UnifyCX is pioneering AI-driven customer experience solutions at scale, blending cutting-edge technology with human-centric design. Our AI Engineering team is looking for an ML Engineer to drive our most ambitious projects forward! Our environment is dynamic and experiment-driven, and you will have the opportunity to shape solutions that transform the CX landscape for businesses worldwide. If you’re excited about being on the cutting edge of AI research and deployment, we want to hear from you!
About the Role
As a Sr Machine Learning Engineer, you will partner with product, UX, backend and infrastructure teams to design and deploy production-grade recommendation and retrieval engines that power AI–human interactions across text, voice, and multimodal channels. You will build intelligent data orchestration pipelines that ingest, process, and materialize structured, unstructured, scalar and vector data modalities—enabling seamless end-to-end ML workflows from data capture through inference and feedback loops. You will also architect and implement agentic workflow frameworks for autonomous, multi-step decision-making in conversational services.
Responsibilities
- Design and deploy production-grade recommendation and retrieval engines.
- Build intelligent data orchestration pipelines.
- Architect and implement agentic workflow frameworks.
- Prototype, optimize, and deploy high-performance models at scale – balancing low-latency, high-throughput SLAs with robust governance, monitoring, and reliability.
Qualifications
- Master’s degree in Computer Science, Machine Learning, Statistics or related field with applied AI/system integration focus.
- 1–2 years of industry experience building and shipping production grade ML systems—especially recommendation or retrieval engines for conversational use cases.
Required Skills
- Proficiency in Python and hands-on experience with PyTorch or TensorFlow: custom architectures, performance tuning, scalable serving.
- Demonstrated ability to build data orchestration pipelines for diverse modalities (structured, unstructured, vector, scalar) and integrate them into ML workflows.
- Practical knowledge of Transformer-based models, embedding techniques and retrieval libraries, and multimodal RAG based systems.
- Experience designing agentic or multi-step orchestration frameworks (e.g., LangChain, custom agent controllers) to automate complex processes.
- Understanding of system guardrails for designing controlled dynamic workflows
Preferred Skills
- Familiarity with MLOps and CI/CD tooling for automated deployment, monitoring, rollback, and model governance.
- Knowledge of privacy-preserving ML (federated learning, differential privacy) and ethical guardrails for regulated industries.
- Strong data engineering skills: experience with large-scale ETL and streaming pipelines (e.g., Apache Spark, Airflow, Kafka) to ingest, clean, and transform data for ML applications.
- Experience with distributed serving frameworks and container/orchestration platforms (Kubernetes, serverless).
For pay transparency purposes, the base salary for this full time position is $180,000 – $250,000. We believe in fair compensation concomitant with candidate experience and location.
