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About The Role In this role, you will help turn advanced machine learning ideas into reliable production solutions that deliver real business value. You will take ownership of building and scaling end-to-end ML systems while working within SoftServe’s AI and Data Science Center of Excellence, a community of more than 170 AI and ML specialists. Your work will connect applied research with production delivery through close collaboration with engineers, data scientists, and clients to create practical AI solutions with measurable impact Responsibilities Design end-to-end machine learning pipelines covering data ingestion, feature engineering, model training, optimization, and production deployment to support reliable AI solutions Build and maintain LLMOps pipelines using experiment tracking and observability tools to improve model reproducibility, prompt management, and production visibility across ML systems Collaborate with data scientists, engineers, and clients to transform business requirements into production-ready solutions for NLP, retrieval-augmented generation, and multimodal AI applications Develop agentic systems and multi-agent workflows using frameworks such as LangGraph, CrewAI, or similar technologies to support autonomous AI capabilities at production scale Enhance machine learning infrastructure by maintaining CI/CD/CT pipelines, cloud environments, data stores, monitoring processes, and security practices that support dependable operations Integrate and package machine learning services into production applications while ensuring reliability, maintainability, and long-term operational stability Operate workflow orchestration platforms such as Databricks Jobs and Workflows, Kubeflow, or Airflow to automate, schedule, and monitor machine learning pipeline execution Requirements Strong experience with building and deploying production-grade machine learning solutions, supported by at least three years of hands-on industry experience Advanced knowledge of Python across the machine learning and data science ecosystem, including model development, packaging, and service integration Hands-on expertise with LLMOps, AgentOps, and experiment tracking tools such as MLflow, Langfuse, LangSmith, and Weights & Biases Solid understanding of CI/CD/CT practices for machine learning systems together with workflow orchestration platforms including Databricks Workflows, Kubeflow, or Airflow Proven experience with cloud-based AI and machine learning services on AWS, Azure, or Google Cloud Platform Working knowledge of agentic AI frameworks such as LangGraph, CrewAI, or similar technologies for building autonomous and multi-agent systems Master’s degree in Computer Science or a related field Strong communication skills with Upper-Intermediate or higher English proficiency, enabling effective collaboration with cross-functional teams and clients SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.