Machine Learning Engineer
hace 12 horas
Fort Myers
About the Role We are seeking an experienced Machine Learning Engineer with a minimum of 5 years of professional experience to design, develop, deploy, and optimize scalable machine learning systems and AI-powered applications within an enterprise technology environment. This opportunity is ideal for an engineer with strong expertise in Python, Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), MLOps, Cloud Computing, and Production Model Deployment who enjoys transforming advanced algorithms into reliable, high-performance software solutions. The Machine Learning Engineer will collaborate with Data Scientists, AI Researchers, Software Engineers, Data Engineers, Cloud Infrastructure teams, and Product Managers to build intelligent systems supporting predictive analytics, automation, recommendation engines, natural language processing, and emerging Generative AI applications. The ideal candidate combines advanced programming skills, applied machine learning expertise, strong software engineering practices, and experience delivering production-ready AI solutions. Essential Duties and Responsibilities • Design, develop, train, evaluate, and deploy machine learning models for enterprise applications., • Build scalable machine learning pipelines supporting data preprocessing, feature engineering, model training, evaluation, and inference., • Develop production-ready ML solutions using Python, PyTorch, TensorFlow, scikit-learn, and comparable frameworks., • Implement and optimize deep learning architectures for classification, forecasting, recommendation systems, and natural language processing., • Deploy machine learning models through APIs, microservices, batch-processing systems, and real-time inference services., • Develop and maintain MLOps workflows, including model versioning, experiment tracking, automated testing, CI/CD, and model monitoring., • Collaborate with Data Engineering teams to ensure reliable data pipelines and feature availability., • Optimize model performance, inference latency, scalability, and cloud resource utilization., • Monitor deployed models for data drift, performance degradation, and operational issues., • Evaluate opportunities to integrate Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI automation into business applications., • Apply responsible AI practices involving model explainability, privacy, security, and reliability., • Participate in architecture reviews, code reviews, technical documentation, and engineering design discussions., • Troubleshoot complex machine learning infrastructure and production model issues., • Collaborate with cross-functional stakeholders to translate business requirements into effective ML solutions. Job Qualifications and Requirements • Minimum 5 years of professional experience in Machine Learning Engineering, Applied Machine Learning, AI Engineering, or a closely related software engineering discipline required., • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Mathematics, Engineering, or a related technical field, or equivalent practical experience., • Advanced proficiency in Python and strong knowledge of software engineering principles., • Hands-on experience with PyTorch, TensorFlow, scikit-learn, XGBoost, or comparable machine learning frameworks., • Experience developing, evaluating, and deploying machine learning models in production environments., • Strong understanding of supervised learning, unsupervised learning, feature engineering, model evaluation, and optimization techniques., • Experience with MLOps, MLflow, Kubeflow, model registries, experiment tracking, or comparable ML lifecycle tools., • Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP)., • Experience with Docker, Kubernetes, REST APIs, CI/CD pipelines, and scalable deployment practices., • Strong knowledge of SQL, data processing, and distributed computing fundamentals., • Familiarity with Apache Spark, Databricks, Airflow, or related data processing and orchestration technologies., • Understanding of model monitoring, observability, data drift, and production reliability., • Experience with Generative AI, LLMs, NLP, Hugging Face, vector databases, or RAG architectures is advantageous., • Strong debugging, analytical problem-solving, and technical communication skills. Personal Capabilities and Qualifications • Strong analytical reasoning and advanced technical problem-solving abilities., • Ability to translate complex AI and machine learning concepts into practical engineering solutions., • High standards for code quality, model performance, and system reliability., • Strong ownership of machine learning solutions throughout the development lifecycle., • Ability to balance model accuracy, computational efficiency, scalability, and business impact., • Excellent collaboration with engineering, research, product, and data teams., • Effective communication with technical and nontechnical stakeholders., • Ability to work independently within distributed and remote engineering environments., • Commitment to responsible AI development and continuous technical learning. Strategic Support • Contribute to enterprise AI strategy and machine learning platform modernization., • Support development of scalable, reusable ML infrastructure and deployment frameworks., • Help accelerate adoption of intelligent automation and AI-driven business applications., • Evaluate emerging technologies in Generative AI, LLMs, Deep Learning, and MLOps., • Support improvements in model governance, reproducibility, monitoring, and operational efficiency., • Collaborate with technical leadership on AI architecture and long-term engineering roadmaps., • Identify opportunities to improve business outcomes through production machine learning capabilities. Working Conditions • Remote position within the United States., • Full-time position within an enterprise AI and software engineering environment., • Regular virtual collaboration with Machine Learning, Data Science, Software Engineering, Cloud Infrastructure, and Product teams., • Collaboration across multiple U.S. time zones may be required., • Participation in Agile development activities, technical reviews, model releases, and engineering planning sessions., • Occasional production support or scheduled deployment activities may be required., • Responsible handling of confidential enterprise information, proprietary source code, and sensitive datasets is required. Job Function Primary Function: Machine Learning Engineering Specialization: Applied AI, Deep Learning, MLOps & Production ML Systems Workplace: Remote — United States Employment Type: Full-Time Experience Required: Minimum 5 Years Relevant Skills & Keywords: Machine Learning Engineer, ML Engineer, AI Engineer, Artificial Intelligence, Machine Learning, Deep Learning, Python, PyTorch, TensorFlow, scikit-learn, XGBoost, Neural Networks, Natural Language Processing, NLP, Generative AI, Large Language Models, LLMs, Retrieval-Augmented Generation, RAG, Hugging Face, Model Training, Model Evaluation, Model Deployment, Model Serving, MLOps, MLflow, Kubeflow, Feature Engineering, Feature Stores, Model Monitoring, Data Drift, AWS SageMaker, Azure Machine Learning, Google Vertex AI, AWS, Azure, GCP, Docker, Kubernetes, REST APIs, CI/CD, Apache Spark, Databricks, SQL, Distributed Systems, Cloud-Native AI Applications. Compensation & Benefits Compensation will be competitive and determined based on technical experience, qualifications, geographic location, and overall position responsibilities. The total rewards package may include: • Competitive annual base salary, • Performance-based incentives where applicable, • Medical, dental, and vision insurance, • Retirement savings with employer contributions, • Paid time off and company holidays, • Paid parental and family leave, • Life and disability insurance, • Remote-work support and equipment assistance, • Professional development and technical certification support, • AI, machine learning, and cloud training opportunities, • Wellness and employee-assistance programs, • Additional benefits according to company policy Why Join Us Join an enterprise technology environment where Machine Learning and Artificial Intelligence contribute to digital innovation, intelligent automation, advanced analytics, and modern software applications. You will have opportunities to work with modern ML frameworks, cloud platforms, scalable AI infrastructure, and experienced technical professionals while developing solutions that address meaningful business challenges. This position offers technical ownership, exposure to advanced AI technologies, and opportunities to strengthen expertise in Python, PyTorch, TensorFlow, MLOps, Generative AI, LLMs, and cloud-based machine learning systems. For a Machine Learning Engineer with 5+ years of professional experience, this role provides remote flexibility, continued technical growth, and the opportunity to build reliable, scalable machine learning solutions with measurable enterprise impact. Equal Employment Opportunity We are committed to providing equal employment opportunities to qualified applicants without discrimination based on legally protected characteristics. Employment decisions are based on job-related skills, experience, qualifications, and applicable business requirements.