\\\\Introduction\\\\ At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk. \\\\Your role and responsibilities\\\\ Hakkoda is a modern data consultancy that empowers data driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyones input and efforts are valued. We hire outstanding individuals and give them the opportunity to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly-growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!. Role Overview: Develop and train artificial intelligence tools to help automate processes for clients. Duties include designing and programming artificial intelligence systems, testing the machine learning tools and resolving issues with the algorithms and data to ensure the system works correctly. AI tools include chatbots, translations tools, predictive text and virtual assistants. Responsibilities: \\\ AI Solution Design: Collaborate with cross-functional teams to design AI models and algorithms that solve business problems for clients. \\\ Model Development: Build, train, and deploy machine learning models, natural language processing systems, and computer vision applications. \\\ Client Engagement: Understand client requirements, present AI solutions, and work with clients to integrate AI technologies into their business processes. \\\ Data Preprocessing: Clean, analyze, and prepare large datasets for machine learning and AI model training. \\\ Implementation & Deployment: Implement AI solutions and ensure smooth deployment on cloud-based environments, ensuring scalability and performance optimization. \\\ Cloud Management Strategies: Oversee and maintain a deep understanding of various services like AWS, Azure, and GCP. \\\ Collaborative Problem Solving: Work with software development and IT teams to integrate AI models into production systems and ensure their continuous improvement. \\\ AI Research & Innovation: Stay ahead of industry trends and emerging technologies in AI and data science, and leverage this knowledge to drive innovation within the organization \\\ Documentation: Prepare detailed documentation for AI models, algorithms, and implementation processes to ensure knowledge transfer and scalability. Manage and enforce best practices for version control and collaboration tools, such as Github, Bitbucket, and Gitlab. As of April 2025, Hakkoda has been acquired by IBM and will be integrated in the IBM organization. Your recruitment process will be managed by IBM. IBM will be the hiring entity. This role can be performed from anywhere in the US. \\\\Required technical and professional expertise\\\\ \\\ Education: Bachelors degree in Computer Science, Data Science, AI, or related field (Masters or Ph.D. is a plus). \\\ Experience: \\\ Minimum of 3-5 years of experience in AI engineering, machine learning, or related fields. \\\ Experience working in a professional services or consulting environment is highly desirable. \\\ Technical Skills: \\\ Expert proficiency in Python, with experience in other programming languages highly valued. \\\ Deep knowledge and practical implementation of advanced AI technologies, including Langchain, Vector Stores, etc. \\\ Strong understanding of AI/ML algorithms (supervised/unsupervised learning, reinforcement learning). \\\ Familiarity with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models. \\\ Experience with data analytics and data engineering tools (SQL, Hadoop, Spark). \\\ Proven experience in planning, developing, and implementing complex data pipelines. \\\ Soft Skills: \\\ Strong communication skills with the ability to explain complex AI concepts to non-technical stakeholders. \\\ Ability to work in a fast-paced, client-facing environment with attention to detail. \\\ Strong problem-solving skills and the ability to think creatively to solve client challenges. \\\\Preferred technical and professional experience\\\\ \\\ Knowledge of industry-specific AI applications (e.g., healthcare, financial services, supply chain, retail/CPG). \\\ Experience with natural language processing (NLP) and computer vision technologies. \\\* Previous experience in an Agile or Scrum environment. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

A Bachelor's degree in Computer Science, Data Science, AI, or a related field is required, with a Master's or Ph.D. being a plus. The role necessitates a minimum of 3-5 years of experience in AI engineering, machine learning, or related fields. Experience in a professional services or consulting environment is highly desirable. Essential technical skills include expert proficiency in Python, deep knowledge of advanced AI technologies like Langchain and Vector Stores, and a strong understanding of AI/ML algorithms. Familiarity with cloud platforms such as AWS, Azure, and Google Cloud for deploying AI models, along with experience in data analytics and engineering tools like SQL, Hadoop, and Spark, is also crucial. Proven experience in planning, developing, and implementing complex data pipelines is expected.