AI & ML Career Opportunities – Engineers, Scientists & Product Managers

We're expanding our AI/ML team and are looking for talented professionals to join us in building ground-breaking innovative, data-driven solutions. If you're passionate about Artificial Intelligence, Data Science, and making an impact, we'd love to hear from you.

We are hiring for the following positions

• Artificial Intelligence (AI) Engineer (3-5 years experience)
• AI Product Manager (7-9 years experience)
• Data Scientist (3-6 years experience)
• Machine Learning Engineer (3-6 years experience)

Employment Type
: Full-time

Location:
Pune/Iselin, NJ

Work Mode
: Hybrid

Artificial Intelligence (AI) Engineer

Responsibilities:

• Build, train, and optimize AI/ML models for a variety of use cases (e.g., predictive analytics, recommendation systems, computer vision, NLP).
• Implement and fine-tune large language models (LLMs) such as GPT, Claude, Gemini, and open-source alternatives for chatbots, summarization, content generation, and automation.
• Collect, clean, and preprocess structured and unstructured data for AI model training.
• Deploy AI solutions into production environments and integrate with existing systems via APIs or cloud platforms.
• Optimize AI models for accuracy, efficiency, and scalability.
• Work with stakeholders to define AI solution requirements, KPIs, and expected outcomes.

Required Skills:

• Proficiency in Python (TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain) and familiarity with R, Java, or C++.
• Strong knowledge of machine learning algorithms, deep learning architectures (CNN, RNN, Transformers), NLP, and computer vision.
• Experience with SQL, NoSQL, and big data frameworks (Spark, Hadoop).
• Hands-on experience with AWS AI/ML, Azure AI, or Google Cloud AI services.
• Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).

AI Product Manager

Responsibilities:

• Define the AI product vision, roadmap, and success metrics aligned with company objectives.
• Identify emerging AI trends, competitive landscape, and customer needs to guide product direction.
• Work closely with leadership, engineering, and business teams to prioritize AI product features.
• Translate business requirements into clear, actionable product specifications for AI/ML teams.
• Ensure AI models are successfully integrated into products, with measurable performance improvements.
• Oversee the end-to-end product lifecycle from ideation to launch and post-release optimization.
• Collaborate with design teams to create intuitive, AI-driven user experiences.
• Analyze product performance and user feedback to guide iterative improvements.

Required Skills

• 7+ years in product management, with at least 2 years focused on AI/ML products.
• Familiarity with machine learning concepts, LLMs, computer vision, NLP, and generative AI applications.
• Ability to work closely with data scientists and engineers, understanding technical trade-offs.
• Proficiency in data-driven decision-making, KPI definition, and testing.
• Strong storytelling skills to explain AI capabilities and limitations to both technical and non-technical audiences.

Data Scientist

Responsibilities:

• Collect, clean, and analyze large structured and unstructured datasets.
• Build, train, and validate predictive, classification, and generative models using ML and deep learning frameworks.
• Identify and create optimal input variables to improve model performance.
• Communicate insights effectively using data visualization tools and dashboards.
• Partner with engineers to deploy AI models into production and ensure scalability.
• Stay updated with emerging trends in AI/ML, big data technologies, and advanced analytics.
• Translate analytical findings into actionable recommendations for stakeholders.

Required Skills:

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch), SQL; familiarity with R is a plus.
• Experience in supervised/unsupervised learning, NLP, and deep learning architectures.
• Knowledge of big data tools (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Proficiency in Tableau, Power BI, or similar tools.
• Strong analytical thinking and structured problem-solving approach.

Machine Learning Engineer

Responsibilities:

• Design, train, and optimize machine learning and deep learning models for real-world applications.
• Build and maintain data preprocessing, transformation, and feature engineering pipelines.
• Deploy ML models to production using cloud services and MLOps best practices.
• Monitor model performance, retrain when necessary, and improve accuracy and latency.
• Work with APIs, microservices, and applications to integrate ML models into production systems.
• Partner with data scientists to translate research into production-ready solutions.
• Conduct experiments to evaluate algorithms and architectures for optimal results.
• Maintain clear technical documentation for models, pipelines, and deployment processes.

Required Skills:

• Proficiency in Python (TensorFlow, PyTorch, Scikit-learn) and experience with Java, C++, or Go is a plus.
• Solid understanding of algorithms, deep learning architectures (CNNs, RNNs, Transformers), and NLP techniques.
• Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop).
• Proficiency with Docker, Kubernetes, MLflow, and model deployment pipelines.
• Experience with AWS SageMaker, Azure ML, or Google Vertex AI.