TalentsToday

Location - Armenia

Duration - 6+ months
Start Date - ASAP

About the Role

We are looking for a skilled Machine Learning Engineer to join a long-term project focused on building and improving ML-driven products. The ideal candidate has strong hands-on experience with production ML systems, LLMs, and generative AI technologies, and is comfortable working independently in a fast-paced environment.

Requirements

• 3+ years of experience in applied Machine Learning in production environments
• Strong experience with:
  • LLMs
  • Generative AI
  • Embeddings
  • NLP
• Basic experience with Computer Vision / image generation
• Strong Python skills (APIs, pipelines, deployment)
• Experience working with data from multiple and diverse sources
• Ability to evaluate and measure model quality
• Product-oriented mindset with focus on business outcomes, not only ML metrics

• High level of ownership and independence

   

Nice-to-Have Skills

• Experience with content or ad generation systems
• Reverse-engineering of ML-based products
• Model fine-tuning
• MLOps experience (logging, monitoring, experiment tracking)

Senior AI Engineer
An AI consulting group that builds serious, production-grade systems for companies ready to operationalize artificial intelligence across their business. We do not build gimmicks. The main focus is on custom AI solutions that integrate directly into operations and drive measurable results.
 

We’re looking for a Senior AI Engineer for one of our clients  - an AI consulting group that builds production-grade systems for companies ready to operationalize artificial intelligence across their business. This is a hands-on role for someone who doesn’t just experiment with AI, but has built, deployed, and optimized real AI systems in complex, production environments.

This role is for someone who takes full ownership of AI systems - from architecture to performance. You’ll work at the intersection of LLMs, distributed data processing, and backend systems, building scalable AI pipelines and knowledge systems in a high-impact environment where performance, reliability, and flexibility (including airgapped deployments) matter.

Your responsibilities will include:

• Design and build distributed data pipelines (Apache Beam, Python) for large-scale document and model processing;
• Implement horizontally scalable LLM-powered extraction workflows across thousands of entities;
• Build runner-agnostic pipelines that run across multiple environments (local, cloud, on-prem);
• Design and implement entity resolution and cross-referencing systems with confidence scoring;
  Architect and build graph-based Knowledge Bases (Dgraph or similar), including schema design and query optimization;
• Develop pluggable LLM extractor frameworks (classification, relationships, completeness, document linking);
• Build abstraction layers for LLM providers (Anthropic Claude, Google Gemini, local models via Ollama/vLLM);
• Optimize LLM usage for cost, latency, and reliability in production environments;
• Design and implement backend service layers (Go-based APIs) connecting AI pipelines with agent systems;
• Ensure observability, debugging, and performance monitoring across distributed AI systems;
• Package and deploy systems using Docker (docker-compose, containerized environments);
• Collaborate directly with client teams on integrations, validation, and production rollout.

What we expect from you:

• 5–8+ years of experience in AI Engineering, Data Engineering, or Applied ML Infrastructure;
• Expert-level Python;
• Strong experience with distributed processing frameworks (Apache Beam preferred; Spark/Flink acceptable);
• Hands-on experience integrating LLMs in production (prompting, orchestration, provider abstraction);
• Experience with graph databases (Dgraph, Neo4j, JanusGraph, or similar);
• Strong understanding of distributed systems, parallel processing, and large-scale data pipelines;
• Solid SQL and data modeling fundamentals;
• Experience with Docker and containerized deployments;
• Experience with cloud platforms (GCP preferred, AWS/Azure acceptable);
• Strong backend/system design mindset (performance, scalability, reliability);
• Ability to work independently and take ownership without micromanagement;
• Strong problem-solving skills in complex, ambiguous environments;
• English level: B2+ (C1 preferred);
• Availability to overlap with US business hours.

Our Customer offers:
- Four-month full-time contract engagement;

- Remote work with overlap in US business hours;

- High-impact project with direct influence on production AI systems;

- Close collaboration with client’s product and engineering teams;

- Opportunity to build core infrastructure for real-world AI applications — not prototypes.

Location: US 
Project Duration: June 8, 2026 – July 24, 2026
В2В Contract
 

🎯 Key Responsibilities

• Solution Design & Configuration: Design and configure customized Salesforce solutions using both declarative tools and programmatic development.
• Custom Development: Develop custom applications using Apex, Lightning Web Components (LWC), JavaScript, and HTML/CSS to meet complex requirements.
• Release Management: Manage the full system release schedule and rollout process for assigned applications and projects.
• Platform Optimization: Research Salesforce capabilities to provide gap analyses and recommend features that improve organizational effectiveness.
• Integrations: Lead the integration of Salesforce with third-party systems and AppExchange products to create a unified digital ecosystem.
• Documentation: Author and maintain comprehensive system configuration documentation to ensure long-term scalability and support.
• Technical Leadership: Partner with distributed delivery teams as a technical lead to drive best practices in automation and process improvement.
   

📋 Qualifications & Skills

• Experience: 5 years of total Salesforce experience with a strong focus on technical consulting and solution design.
• LWC: 2+ years of hands-on experience developing with Lightning Web Components.
• Certifications: Possession of at least 4 Salesforce certifications, demonstrating deep platform expertise.
• Development Skills: Proficiency in Salesforce development including Apex Classes, Triggers, Web Services, and Aura Components.
• Data Tools: Proven experience using data tools such as Data Loader and DemandTools for complex migration and integration tasks.
• Leadership: Strong background in lead roles, such as Lead Developer or Technical Lead, within distributed delivery models.
• Architecture: Solid understanding of software architecture principles, including object-oriented design and modularity.
• Communication: Excellent technical writing skills and the ability to translate complex application logic into clear documentation.

❗️ Critical Requirements❗️

• Must have end-to-end Marketing Cloud and SF Data Cloud experience.
   

Don't hesitate to reach out with any questions. I'd be happy to assist.