Machine Learning Engineer (MLOps)

Posted 5 Days Ago
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Panama City, Panamá, PAN
In-Office
Expert/Leader
Professional Services • Consulting
The Role
Develop and operate scalable machine learning systems in production. Responsibilities include designing MLOps infrastructure, automated training and deployment pipelines, model monitoring and observability, governance, validation, performance optimization, and workflow automation. The role collaborates with data scientists and engineers and uses Azure, MLflow, Kubeflow, CI/CD, orchestration tools, and AI-assisted development technologies.
Summary Generated by Built In

Langan provides expert land development engineering and environmental consulting services for major developers, renewable energy producers, energy companies, corporations, healthcare systems, colleges/universities, and large infrastructure programs throughout the U.S. and around the world. Our employees collaborate seamlessly among 50+ offices and gain valuable hands-on experience that fosters career growth. Langan culture is entrepreneurial from advancing innovative technical solutions, to participating in robust training and knowledge sharing, to making progressive change within the communities we live and work.

Consistently ranked among the top ten “Best Firms to Work For” and Engineering News-Record’s top 50 firms worldwide, Langan attracts and retains the best talent in the industry. Employees thrive at Langan, a firm that fosters an inclusive and supportive work environment for all; prioritizes wellbeing, health, and safety; encourages volunteerism and philanthropy; offers workplace flexibility, along with carbon-neutral office spaces; and empowers individuals to contribute their skills and knowledge to make impactful contributions.


Job Summary

Langan is seeking a Machine Learning Engineer (MLOps) to join its collaborative Information Technology team. This individual will support the development, deployment, and optimization of machine learning systems, ensuring scalability, reliability, and continuous improvement in production environments. 

Job Responsibilities
  • Explore, design, and implement machine learning infrastructure frameworks and tools to accelerate model development and delivery. 
  • Champion model observability, monitoring, and feedback loops to ensure continuous model performance and health. 
  • Design and maintain automated pipelines for model training, evaluation, versioning, and deployment. 
  • Collaborate with data scientists and engineers to define requirements, metrics, and deliver high-impact solutions. 
  • Enforce model governance, validation standards, and best practices to ensure reproducibility and compliance. 
  • Identify and resolve bottlenecks in ML workflows, improving reliability, latency, and system performance. 
  • Leverage AI-assisted tools and LLM-based technologies to improve development efficiency and automate workflows. 
Qualifications
  • Bachelor’s degree in Computer Science, Software Engineering, Machine Learning, Statistics, or a related field. 
  • 8+ years of experience in software engineering with exposure to large-scale system design and ML systems. 
  • Strong experience with Microsoft Azure, distributed systems, and databases (SQL/NoSQL). 
  • Hands-on experience with MLOps tools such as Azure Machine Learning, MLflow, and Kubeflow. 
  • Proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn. 
  • Experience building CI/CD pipelines for ML workflows (e.g., Azure DevOps, GitHub Actions, ArgoCD). 
  • Experience with data orchestration tools such as Azure Data Factory, Airflow, or Prefect. 
  • Strong analytical, problem-solving, and communication skills. 

 

Preferred Qualifications: 

  • 10+ years of experience building scalable ML systems in production environments. 
  • Experience with model monitoring, drift detection, and observability practices. 
  • Strong cross-functional collaboration skills across engineering and data science teams. 
  • Experience using AI-assisted development tools to support coding, documentation, and testing workflows.

Langan provides a rich array of programs and benefits to help its employees advance their careers and enhance the quality of their lives. Our comprehensive compensation package includes full-time employment company paid medical, dental, and vision coverage; life insurance, short- and long-term disability insurance, and paid pregnancy disability leave; 401(k)/Roth with company match; paid time off including parental and military leave; employee referral and professional license bonuses; and educational reimbursement.

Langan offers employee resource groups; flexible work schedules; extensive training; wellness programs; buddy and mentoring programs; and much more!

Langan is committed to providing equal employment opportunities to all qualified applicants and employees, including individuals with disabilities and protected veterans. We believe that an inclusive workplace is essential for the well-being and success of our employees.

Please review our Applicant Privacy Notice at Collection to understand how we collect, use, and retain your personal information:  https://www.langan.com/langan-notice-at-collection



Skills Required

  • Bachelor’s degree in Computer Science, Software Engineering, Machine Learning, Statistics, or a related field
  • 8+ years of software engineering experience with exposure to large-scale system design and machine learning systems
  • Strong experience with Microsoft Azure, distributed systems, and SQL/NoSQL databases
  • Hands-on experience with Azure Machine Learning, MLflow, and Kubeflow
  • Proficiency in Python and familiarity with TensorFlow, PyTorch, or scikit-learn
  • Experience building CI/CD pipelines for machine learning workflows using tools such as Azure DevOps, GitHub Actions, or ArgoCD
  • Experience with data orchestration tools such as Azure Data Factory, Airflow, or Prefect
  • Strong analytical, problem-solving, and communication skills
  • 10+ years of experience building scalable machine learning systems in production environments
  • Experience with model monitoring, drift detection, and observability practices
  • Strong cross-functional collaboration across engineering and data science teams
  • Experience using AI-assisted development tools for coding, documentation, and testing workflows
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The Company
2,300 Employees
Year Founded: 1970

What We Do

Langan is a premier provider of integrated land development engineering, environmental consulting, and digital solutions. The firm supplies engineering and environmental services supporting land development projects, corporate real estate portfolios, and the energy industry. It also partners with clients as a technical and regulatory advocate, helping them address complex environmental challenges through site assessment, design, and remediation, as well as related project needs.

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