Machine Learning Engineer
Machine Learning Engineer
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Job Description
Machine Learning Engineer
Overview
The Machine Learning Engineer plays a critical role in advancing Netfors AI and data initiatives by developing and deploying productiongrade ML models within our AWSbased infrastructure. This position focuses on implementing retrievalaugmented generation (RAG) for virtual agents optimizing MLOps pipelines and ensuring scalability and efficiency in AIdriven workflows. The ML Engineer collaborates with Data Engineers Software Developers and Business Leaders to enhance Netfors data intelligence capabilities supporting key initiatives like the OLTP/OLAP environment data governance and AIpowered automation.
Key Responsibilities
1. ML Model Development & Deployment
- Design develop and deploy ML models for natural language processing (NLP) large language models (LLMs) and predictive analytics.
- Implement retrievalaugmented generation (RAG) methodologies for virtual call center agents using vector databases and embeddings.
- Optimize model performance for low latency and cost efficiency in production environments.
2. MLOps & Cloud Deployment
- Deploy and manage models using AWS services such as SageMaker Bedrock Lambda ECS Fargate and Step Functions.
- Automate model retraining monitoring and deployment pipelines using CI/CD (GitHub Actions AWS CodePipeline).
- Develop scalable feature engineering and data preprocessing pipelines using AWS Glue Athena and Redshift.
3. Data Integration & Engineering
- Collaborate with Data Engineers to integrate ML workflows with OLAP and OLTP data environments.
- Implement efficient data retrieval transformation and ingestion processes from structured and unstructured sources.
- Work with dbt SQL and Python to support analytics and model training data preparation.
4. AI Governance & Model Monitoring
- Establish model versioning logging and performance tracking frameworks.
- Ensure compliance with AI ethics bias mitigation and governance policies.
- Work with Data Governance initiatives to document and maintain AI/ML assets.
5. Collaboration & Stakeholder Engagement
- Partner with business leaders and service delivery teams to align ML initiatives with strategic goals.
- Educate internal teams on ML best practices model interpretability and AIdriven decisionmaking.
- Provide technical leadership on emerging AI trends tools and methodologies.
Skills and Qualifications
Technical Skills
- Proven experience deploying at least one production ML product (LLMs NLP predictive modeling etc..
- 3 years of experience in ML engineering AI research or data science.
- AWS Expertise experience with at least two or more AWS services (SageMaker Bedrock Lambda Glue Athena Redshift ECS Fargate).
- Strong programming skills in Python (TensorFlow PyTorch Scikitlearn) and SQL.
MLOps experience CI/CD model monitoring data pipelines and inference optimization. - Knowledge of retrievalaugmented generation (RAG) and vector database integration.
- Familiarity with API development for model serving and realtime inference.
Soft Skills
- Strong problemsolving and analytical skills with a focus on productionscale ML solutions.
- Excellent communication and documentation skills in English for collaboration with technical and nontechnical stakeholders. A proactive approach to learning and innovation in AI and cloud computing.
Key Performance Indicators (KPIs)
- Model Performance: Ensure production models meet 99 uptime and SLA requirements.
- Scalability: Optimize ML workloads to reduce cost and improve efficiency.
- AI Governance: Maintain compliance with internal and external AI policies.
- Stakeholder Engagement: Positive feedback from internal teams on ML solutions.
- Innovation Contribution: Implementation of at least two new AIdriven enhancements annually.
Additional Information
Reporting
This role reports to the Director of Data Operations and collaborates closely with the Data Engineering and Software Development teams.
Work Environment
- Remotefriendly position with occasional inoffice collaboration.
- Requires the ability to work in a fastpaced cloudfirst environment.
- Low to moderate noise level in work setting.
Expected Hours of Work
- Fulltime workfromhome position.
- May require occasional travel overtime and weekend hours for major deployments.
Travel
Minimal travel primarily local and during business hours.
Other Duties
This job description is not exhaustive and may evolve with business needs. Employees may be required to perform additional duties as needed.
Top 5 required tech and soft skills:
Technical Skills (Musthave competencies)
- Machine Learning Model Development Experience developing and deploying ML models particularly in NLP LLMs and predictive analytics.
- AWS ML & Cloud Expertise Handson experience with AWS SageMaker Bedrock Lambda Glue Athena and Redshift for model training deployment and inference.
- MLOps & Automation Strong knowledge of CI/CD (GitHub Actions AWS CodePipeline) model monitoring and automated retraining pipelines.
- RetrievalAugmented Generation (RAG) & Vector Databases Practical experience working with RAG methodologies embeddings and vector database integration.
- Python & SQL Proficiency Strong coding ability in Python (TensorFlow PyTorch Scikitlearn) and SQL for data manipulation and feature engineering.
Soft Skills (Key behaviors and mindset)
- ProblemSolving & Analytical Thinking Ability to optimize models troubleshoot performance issues and innovate AIdriven solutions.
- Communication & Stakeholder Engagement Effectively collaborates with data engineers business leaders and service teams to align ML solutions with company goals.
- Proactive Learning & Adaptability Stays ahead of AI advancements adapts to evolving ML tools and continuously improves workflows.
- AI Governance & Ethical Considerations Awareness of AI bias mitigation compliance and responsible AI practices.
- Leadership & Knowledge Sharing Capable of mentoring teams documenting processes and presenting complex ML concepts to nontechnical audiences.
DISCLAIMER
This job description is a summary of the primary duties and responsibilities of the job and position. It is not intended to be a comprehensive or allinclusive listing of duties and responsibilities.
Netfor Inc. is an equal opportunity employer. All applicants will be considered for employment without attention to race color religion sex sexual orientation gender identity national origin veteran or disability status.
Netfor Inc. participates in EVerify.
Netfor Inc. will not sponsor applicants for work visas.
Required Experience:
Senior IC
Employment Type
Full-Time
