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Job Title: Mid Machine Learning Engineer Key Skills: Python, Machine Learning, AWS SageMaker, SQL, ML Pipelines, Model Deployment, Model Monitoring, Git, MLOps Experience: +2 years of experience. Location: Costa Rica, Peru, Colombia, Bolivia. Work Mode: Remote. At Coforge, we are hiring Mid Machine Learning Engineer (#22519) with the following skill set. Key Responsibilities Build, deploy, and maintain production-grade machine learning models and pipelines. Develop scalable ML solutions using Python and cloud-based machine learning platforms such as AWS SageMaker. Monitor model performance and troubleshoot production ML environments to ensure reliability and scalability. Collaborate with cross-functional teams to deliver data-driven solutions in an Agile environment. Required Skills & Qualifications 2+ years of experience building and maintaining production machine learning models. Strong Python programming skills. Hands-on experience with AWS SageMaker or another enterprise ML platform such as Vertex AI or Azure ML. Proven experience deploying and monitoring ML models in production environments. Advanced SQL skills. Experience with Git and version control. Experience working independently in production environments. Strong understanding of production ML pipelines and deployment best practices. Strong communication and collaboration skills. Preferred Skills Experience with MLOps tools such as MLflow, Airflow, or dbt. Experience with Snowflake. Experience in marketing, growth, experimentation, or causal inference. Experience with LLMs or AI agents. Familiarity with Agile development practices. Experience building scalable ML solutions in enterprise environments. Posted On: 12-08-2026 At Coforge, we hire professionals solely based on their skills and qualifications, and we do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.
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.