Talantix.io
Dexian DISYS•07.02.26
AI SCORE 8.5

Data and Machine Learning Operations Engineer - Remote

$120K–$150K/year
RemoteAI/Big Data
AWS•PostgreSQL•Docker•Terraform•Prometheus•AI Pipelines•Data Engineering•ML Ops

About the Role

We're hiring a Data and Machine Learning Operations Engineer to join our dynamic team remotely. In this role, you'll support data preparation and AI workflow integration, ensuring that AI pipelines are performant and secure. This Data and Machine Learning Operations Engineer position offers you the opportunity to work with cutting-edge technologies and contribute to high-impact projects.

What You'll Do

  • Prepare structured and unstructured data for RAG pipelines.
  • Configure and manage vector databases and embeddings.
  • Collaborate with AI engineers to integrate data into demo workflows.
  • Ensure pipeline reliability, reproducibility, and observability.
  • Support versioning, experimentation, and deployment infrastructure.

Requirements

  • 3-5 years of experience in ML Ops, Data Engineering, or AI pipeline operations.
  • Familiarity with LLM tuning, prompt engineering, or semantic search.
  • Experience with cloud platforms (AWS/Google Cloud Platform/Azure).
  • Understanding of security and privacy in AI data pipelines.
  • Comfortable working on short-term, high-impact innovation sprints.

Nice to Have

  • Experience with AWS Bedrock and Anthropic Claude models.
  • Knowledge of PostgreSQL (RDS) and AWS S3.
  • Familiarity with Terraform, Docker, and monitoring tools like Prometheus.

What We Offer

  • Competitive salary ranging from $120,000 to $150,000 annually.
  • Fully remote work environment with flexible hours.
  • Opportunity to work with a diverse team of professionals.
  • Access to cutting-edge technologies and tools.
  • Comprehensive health benefits and professional development opportunities.
Why This Job8.5 of 10

This role offers a competitive salary and the opportunity to work remotely on innovative AI projects, making it an attractive position for tech professionals.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in AWS services, particularly in setting up scalable data pipelines and managing cloud infrastructure, with hands-on experience in services like S3 and EC2.

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Strong familiarity with containerization technologies such as Docker and orchestration tools like Terraform, enabling efficient deployment and infrastructure management in a remote work environment.

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Experience with monitoring and performance optimization using Prometheus, combined with a mindset geared towards continuous improvement in AI pipeline efficiency and security.

Learning Resources

→AWS Certified Solutions Architect - Associate 2023course
→PostgreSQL Tutorialguide
→Docker for Data Science: Building Data Science Applicationsarticle

Career Path

Data and Machine Learning Operations Engineer(Now)→Machine Learning Engineer(1-2 years)→Lead Data Engineer(3-5 years)

Market Overview

AWS Market Size 2024
$100B
Annual Growth of AWS Services
24.5%
AI Adoption in Cloud Services
65%
Investment in Data Engineering Tools
+32%
Labour Demand for ML Ops Roles
+35%
Avg Salary for Data and ML Ops Engineers
$120K

Skills & Requirements

Required
AWSPostgreSQLDocker
Growing in Demand
KubernetesApache KafkaML Frameworks (e.g., TensorFlow, PyTorch)
Declining
HadoopRDBMS-specific optimization (e.g., Oracle SQL tuning)

Domain Trends

Rise of Serverless Architectures
Serverless computing is gaining traction, with over 40% of organizations adopting AWS Lambda for data processing tasks.
Increased Focus on Data Governance
Data governance frameworks are being prioritized, with 58% of companies integrating AI-driven compliance tools.
Expansion of Edge Computing
Edge computing is expected to grow by 30% in the next two years, driven by the need for real-time data processing in ML applications.

Industry News

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