Machine Learning Engineer

Job Description

This job posting has expired and no longer accepting applications.

Position Overview

ShyftLabs is seeking an experienced Machine Learning Engineer (AI & Conversational Systems) to join our growing team in Atlanta. In this role, you will design, build, and maintain scalable ML infrastructure while leading initiatives in AI-driven solutions, natural language processing (NLP), and chatbot development. You will deploy production-ready machine learning and conversational AI systems that drive measurable business impact for Fortune 500 clients. This position requires deep expertise in cloud platforms, ML operations, and end-to-end pipeline development, with a strong focus on AI engineering and conversational AI applications.

About ShyftLabs

Founded in early 2020, ShyftLabs is a growing data product company working primarily with Fortune 500 enterprises. We deliver digital solutions that accelerate business growth across industries, with a strong focus on creating value through AI-driven innovation and automation.

Job Responsibilities

AI Engineering & Chatbot Development: Design and implement conversational AI platforms, intelligent chatbots, and NLP-driven solutions to enhance customer engagement and automate business processes.

Design, build, and maintain highly scalable, robust, and efficient cloud infrastructure using AWS services (SageMaker, EC2, S3, Lambda, and other ML-focused AWS offerings).

Develop automation and orchestration of ML pipelines, integrating data ingestion, feature engineering, model training, and deployment processes.

Build and deploy production-ready ML models for applications including pricing optimization, operational efficiency, predictive analytics, and conversational AI.

Implement NLP solutions for tasks such as intent recognition, entity extraction, sentiment analysis, and contextual understanding.

Collaborate with cross-functional teams (data scientists, AI engineers, software developers, and business stakeholders) to deliver end-to-end ML and AI-powered chatbot solutions.

Optimize data processing pipelines and AWS resources to ensure low-latency, cost-effective operation.

Implement monitoring, alerting, and failover strategies to ensure platform reliability and model performance.

Stay updated with emerging trends in AI engineering, large language models (LLMs), conversational AI, and MLOps best practices.

Basic Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Machine Learning, or a related quantitative field.

3+ years of experience in machine learning engineering with a focus on ML infrastructure and AI applications.

Hands-on experience with AWS services including SageMaker, EC2, S3, Lambda, Glue, and other ML-focused AWS offerings.

Proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch, scikit-learn).

Experience with NLP frameworks and libraries (spaCy, Hugging Face Transformers, Rasa, OpenAI APIs, or similar).

Experience designing, building, and deploying chatbots or conversational AI systems at scale.

Knowledge of orchestration tools (Apache Airflow, Kubeflow, or MLflow).

Familiarity with CI/CD pipelines and DevOps tools for continuous integration and deployment.

Experience with containerization and orchestration (Docker, Kubernetes).

Experience with data processing frameworks (Spark, Pandas, Dask).

Strong understanding of ML algorithms, model evaluation, and production deployment challenges.

Experience with real-time ML inference, streaming data, and A/B testing frameworks.

We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is preferably hybrid in Atlanta, with 3+ days per week spent in our downtown office. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse, and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.

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