Industry Data Research & Validation P17

Job Title:Machine Learning Engineer

Location:Hybrid

Job Type:Fulltime

About Us:
Ralliant is at the forefront of leveraging data and AI technologies to drive innovation across Precision Tech Industries. We aim to solve realworld challenges by combining advanced machine learning cloud computing and generative AI to deliver cuttingedge solutions. Were looking for a talented and passionateMLEto join our dynamic team and help us continue to push the boundaries of AI.

Model Deployment & MLOps:

• Design build and maintain machine learning pipelines ensuring continuous integration and deployment (CI/CD) of models in production environments.
• Deploy machine learning models as APIs microservices or serverless functions for realtime inference.
• Manage and scale machine learning workloads using Kubernetes Docker and cloudbased infrastructure (AWS Azure GCP).

Automation & Scripting:

• Automate routine tasks across the ML lifecycle (data preprocessing model training evaluation deployment) using Python Bash and other scripting tools.
• Implement automation for endtoend model management and monitor pipelines for health performance and anomalies.

Cloud Platforms & Infrastructure:

• Utilize cloud platforms (AWS Azure GCP) to optimize the scalability performance and costeffectiveness of ML systems.
• Leverage Infrastructure as Code (IaC) tools like Terraform or CloudFormation to provision and manage cloud resources effectively.

Data Pipelines & Integration:

• Build and maintain robust data pipelines to streamline data ingestion preprocessing and feature engineering.
• Work with both structured and unstructured data sources and databases (SQL NoSQL) to feed data into ML models.

Monitoring Logging & Troubleshooting:

• Set up monitoring and logging systems to track model performance detect anomalies and maintain system health.
• Diagnose and resolve issues across the machine learning pipeline and deployed models.

Collaboration & Communication:

• Collaborate closely with data scientists software engineers and business stakeholders to ensure machine learning models meet the required business objectives and performance standards.
• Effectively communicate complex ML concepts and technical details to nontechnical stakeholders.

GenAI & AI Agents Expertise:

• Stay up to date with the latest trends in Generative AI (e.g. GPT models Diffusion models) and AI agents and bring this expertise into production environments.
• Design and deploy advanced GenAI solutions ensuring they are aligned with business needs and ethical AI principles.

Security & Compliance:

• Implement robust security measures for machine learning models and ensure compliance with relevant data protection and privacy regulations.
• Address vulnerabilities ensuring safe and secure deployment of models in production environments.

Optimization & Cost Management:

• Optimize machine learning resources (compute memory storage) to achieve high performance while minimizing operational costs.
• Regularly review and improve the efficiency of machine learning workflows.

Testing & Validation:

• Develop and execute rigorous testing and validation strategies to ensure the reliability accuracy and fairness of deployed models.
• Use automated testing frameworks to continuously validate model performance.

Required Skills & Qualifications:

• Education: Bachelors or Masters degree in Computer Science Engineering Data Science or a related field.
• Experience:
  • Proven experience (3 years) in machine learning engineering MLOps or related fields.
  • Experience with deploying and managing machine learning models in production using tools like Kubernetes Docker and CI/CD pipelines.
  • Handson experience with cloud platforms (AWS Azure GCP) and infrastructure automation tools (Terraform CloudFormation).
  • Strong coding experience in Python Bash or other scripting languages.
  • Expertise in Generative AI models (e.g. GPT GANs) and their deployment at scale.
  • Experience working with databases (SQL NoSQL) and building data pipelines.
• DevOps & CI/CD:
  • Knowledge of DevOps tools and practices including version control (Git) automated testing and continuous integration/deployment.
• AI Agents: Familiarity with the latest AI agent frameworks and their deployment in realworld applications.
• Data Science Concepts: Solid understanding of GenAINLP Computer Vision machine learning algorithms data structures and model evaluation techniques.
• ProblemSolving: Strong troubleshooting and debugging skills to quickly identify and fix issues within ML pipelines and deployments.
• Collaboration & Communication: Excellent communication skills with the ability to work in a crossfunctional team and explain technical concepts to nontechnical stakeholders.

Preferred Qualifications:

• Certification in Cloud Technologies (AWS Azure GCP) and MLOps platforms.
• Experience with largescale ML systems and distributed computing.
• Understanding of ethical AI practices and AI fairness.
• Familiarity with cuttingedge AI technologies like reinforcement learning AI agents and deep learning.

Technical Skills:

• Proficiency in Python R or other relevant programming languages.
• Strong knowledge of machine learning libraries such as TensorFlow PyTorch Scikitlearn or Keras.
• Experience with SQL and cloudnative data processing tools (e.g. AWS Redshift Azure Synapse Spark).
• Familiarity with DevOps practices and CI/CD pipelines for ML model deployment.

Soft Skills:

• Strong communication skills with the ability to translate complex technical concepts into businessfriendly language.
• Problemsolving mindset with the ability to approach challenges creatively and collaborate with diverse teams.
• Leadership potential or experience mentoring junior team members.

Preferred Qualifications:

• Certification or training in AWS (e.g. AWS Certified Machine Learning) Azure or other cloud services.
• Experience working with containerization technologies like Docker and Kubernetes for model deployment.
• Exposure to the latest trends in AI ethics explainability and fairness.

Company Overview:

Join a dynamic and innovative team at Ralliant a leader in producing hightech measurement instruments and essential sensors. Our brands including Tektronix Qualitrol Sensing Technologies and Pacific Scientific are at the forefront of technological advancements providing critical products that drive innovation across various industries. At Ralliant we are committed to excellence and continuous improvement delivering toptier solutions that meet the evolving needs of our Operating Companies

These are the traits we value:

• You are collaborative proactive adaptable and gritty. You excel at facilitating and reconciling inputs across separated geolocated teams. You balance a passion for deep understanding of innovation with the ability to deliver extraordinary results.
• Ability to Deliver Results: A track record for delivering results with concrete financial and operational objectives as well as the capacity to organize and direct a small team.
• Entrepreneurial Attitude: A proactive outlook that provides the chutzpah needed to overcome barriers creatively problem solve and test conventional thinking.
• Comfort with Ambiguity: A willingness and aptitude for spending time in and thriving with deep uncertainty and environments where there is no clear right answer.
• Passion for Innovation: A demonstrated interest and desire to participate in innovation through personal study onthejob initiative or other endeavors.
• Positive Outlook: A desire to look past the objections in search of the opportunity.
• Strong Communication Skills: An ability to explain new concepts clearly and succinctly able to negotiate and persuade others to your point of view.
• A need for speed; demonstrated ability to make decisions quickly and to act upon them.
• Alongside a team of entrepreneurial highperforming curious people youll deliver breakthrough solutions to drive sustainable growth for Ralliant

Bonus or Equity
This position is also eligible for bonus as part of the total compensation package.