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We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem. In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions. Responsibilities: Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows. Build AI and ML solutions within Palantir Foundry , using Python and existing Foundry pipelines, Ontology objects, and workflows. Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases. Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference. Conduct experiments, evaluate model performance, and iterate on features and model approaches. Integrate AI models into Foundry workflows to surface insights and support business processes. Support model deployment and monitoring by following established team standards and best practices. Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions. Document model behavior, assumptions, and limitations to support transparency and compliance. Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members. Requirements: 3+ years of experience in machine learning, AI engineering, or applied data science. Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch . Practical experience with RAG architectures, vector databases, and retrieval strategies Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization). Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration. Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus. Familiarity with enterprise data environments and collaborative development workflows. Ability to clearly explain model results and AI behavior to non-technical stakeholders. Upper-Intermediate English or higher. Nice to have: Proficiency in Foundry Ontology, Object Builders, and Code Repositories. Experience in big pharma or highly regulated industries. Knowledge of data privacy, compliance, and security best practices in AI applications. Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). We offer*: Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Personalized career growth Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing Education reimbursement Memorable anniversary presents Corporate events and team buildings Other location-specific benefits *not applicable for freelancers
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.